{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d8834a0e",
   "metadata": {},
   "source": [
    "# 时序LSTM模型\n",
    "基于历史消耗数据，预测未来 N 天的原材料消耗趋势，推算补货时间点和采购量。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f094abe5",
   "metadata": {},
   "source": [
    "## 1. 导入必要的库\n",
    "\n",
    "导入PyTorch、NumPy、Matplotlib等库。\n",
    "> pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu130\n",
    "\n",
    "> pip install numpy matplotlib sklearn-learn "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "701fdb20",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[8.1758e-01, 3.5102e-01, 2.6266e-01],\n",
      "        [6.5863e-05, 9.7965e-01, 6.5770e-01],\n",
      "        [5.9349e-01, 7.6911e-01, 7.2913e-01],\n",
      "        [5.7789e-01, 6.7283e-01, 9.0731e-01],\n",
      "        [4.5285e-01, 8.8112e-02, 3.9113e-01]])\n",
      "13.0\n",
      "_CudaDeviceProperties(name='NVIDIA GeForce RTX 5070 Ti', major=12, minor=0, total_memory=16302MB, multi_processor_count=70, uuid=e356cabe-8d6d-45a6-706a-ce45e602f87f, pci_bus_id=2, pci_device_id=0, pci_domain_id=0, L2_cache_size=48MB)\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "x = torch.rand(5, 3)\n",
    "print(x)\n",
    "torch.cuda.is_available()\n",
    "\n",
    "print(torch.version.cuda)  \n",
    "\n",
    "print(torch.cuda.get_device_properties(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1db410bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入库\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "844ed554",
   "metadata": {},
   "source": [
    "## 2. 数据准备与预处理\n",
    "\n",
    "生成正弦波数据，归一化，并切分为适合LSTM输入的序列。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3c9fe709",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 加载原材料消耗数据（示例：可替换为实际数据文件）\n",
    "# import pandas as pd\n",
    "# 假设有一个CSV文件 consumption.csv，包含日期和消耗量两列\n",
    "# df = pd.read_csv('consumption.csv', parse_dates=['date'])\n",
    "# data = df['consumption'].values\n",
    "from matplotlib.font_manager import FontProperties\n",
    "chinese_font = FontProperties(family=\"SimHei\", size=12)\n",
    "\n",
    "np.random.seed(100)\n",
    "data = np.cumsum(np.random.randint(10, 120, size=100))  # 累加模拟消耗趋势\n",
    "plt.plot(data)\n",
    "plt.title('原材料消耗数据', fontproperties=chinese_font)\n",
    "plt.xlabel('天数', fontproperties=chinese_font)\n",
    "plt.ylabel('消耗量', fontproperties=chinese_font)\n",
    "plt.show()\n",
    "\n",
    "# 列向量，归一化\n",
    "data = data.reshape(-1, 1)\n",
    "scaler = MinMaxScaler()\n",
    "data_scaled = scaler.fit_transform(data)\n",
    "\n",
    "# 序列切分\n",
    "def create_dataset(dataset, look_back=20):\n",
    "    X, Y = [], []\n",
    "    for i in range(len(dataset) - look_back):\n",
    "        X.append(dataset[i:(i + look_back), 0])\n",
    "        Y.append(dataset[i + look_back, 0])\n",
    "    return np.array(X), np.array(Y)\n",
    "\n",
    "look_back = 20\n",
    "X, y = create_dataset(data_scaled, look_back)\n",
    "X = X.reshape((X.shape[0], X.shape[1], 1))\n",
    "\n",
    "# 划分训练集和测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# 转为PyTorch张量\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "X_train = torch.tensor(X_train, dtype=torch.float32).to(device)\n",
    "y_train = torch.tensor(y_train, dtype=torch.float32).to(device)\n",
    "X_test = torch.tensor(X_test, dtype=torch.float32).to(device)\n",
    "y_test = torch.tensor(y_test, dtype=torch.float32).to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "182723de",
   "metadata": {},
   "source": [
    "## 3. 构建LSTM模型\n",
    "\n",
    "使用PyTorch定义LSTM网络结构。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1494b101",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LSTMModel(\n",
      "  (lstm): LSTM(1, 50, batch_first=True)\n",
      "  (fc): Linear(in_features=50, out_features=1, bias=True)\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "# 定义LSTM模型\n",
    "class LSTMModel(nn.Module):\n",
    "    def __init__(self, input_size=1, hidden_size=50, output_size=1):\n",
    "        super(LSTMModel, self).__init__()\n",
    "        self.lstm = nn.LSTM(input_size, hidden_size, batch_first=True)\n",
    "        self.fc = nn.Linear(hidden_size, output_size)\n",
    "    def forward(self, x):\n",
    "        # x: (batch, seq_len, input_size)\n",
    "        out, _ = self.lstm(x)\n",
    "        out = out[:, -1, :]  # 取最后一个时间步的输出\n",
    "        out = self.fc(out)\n",
    "        return out\n",
    "\n",
    "model = LSTMModel(input_size=1, hidden_size=50, output_size=1).to(device)\n",
    "print(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "826be085",
   "metadata": {},
   "source": [
    "## 4. 训练模型\n",
    "\n",
    "设置损失函数和优化器，进行模型训练。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "889174ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20, Loss: 0.3615\n",
      "Epoch 2/20, Loss: 0.3164\n",
      "Epoch 3/20, Loss: 0.0441\n",
      "Epoch 4/20, Loss: 0.1434\n",
      "Epoch 5/20, Loss: 0.1728\n",
      "Epoch 6/20, Loss: 0.1502\n",
      "Epoch 7/20, Loss: 0.1007\n",
      "Epoch 8/20, Loss: 0.0452\n",
      "Epoch 9/20, Loss: 0.0396\n",
      "Epoch 10/20, Loss: 0.0613\n",
      "Epoch 11/20, Loss: 0.0389\n",
      "Epoch 12/20, Loss: 0.0278\n",
      "Epoch 13/20, Loss: 0.0303\n",
      "Epoch 14/20, Loss: 0.0331\n",
      "Epoch 15/20, Loss: 0.0334\n",
      "Epoch 16/20, Loss: 0.0310\n",
      "Epoch 17/20, Loss: 0.0274\n",
      "Epoch 18/20, Loss: 0.0256\n",
      "Epoch 19/20, Loss: 0.0247\n",
      "Epoch 20/20, Loss: 0.0249\n"
     ]
    }
   ],
   "source": [
    "# 训练模型\n",
    "criterion = nn.MSELoss()\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.01)\n",
    "\n",
    "num_epochs = 20\n",
    "batch_size = 32\n",
    "train_loss_list = []\n",
    "\n",
    "for epoch in range(num_epochs):\n",
    "    permutation = torch.randperm(X_train.size(0))\n",
    "    epoch_loss = 0\n",
    "    for i in range(0, X_train.size(0), batch_size):\n",
    "        indices = permutation[i:i+batch_size]\n",
    "        batch_x, batch_y = X_train[indices], y_train[indices]\n",
    "        outputs = model(batch_x)\n",
    "        loss = criterion(outputs.squeeze(), batch_y)\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        epoch_loss += loss.item()\n",
    "    avg_loss = epoch_loss / (X_train.size(0) // batch_size)\n",
    "    train_loss_list.append(avg_loss)\n",
    "    print(f\"Epoch {epoch+1}/{num_epochs}, Loss: {avg_loss:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6677a984",
   "metadata": {},
   "source": [
    "## 5. 评估与可视化\n",
    "\n",
    "在测试集上评估模型表现，并可视化训练损失和预测结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5cd3a861",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1EsfExcWJ+44dO5a/e/fu/Pj4+IfGN3Xq1Pzx48c/dH+9evXyf/vtN9VtGvPdu3cfOu7WrVviuY4ePfrQvqysrPzMzEzV3/Xrr78+8vWaMmWKOJ+5uXn+nj17Htr/+eef5//yyy/5OTk5Re7Pzc0Vr5mZmZl4vHLx9/fPv3r16iOfl2EYRtvUoH+0LdAYhmGMDbLuptV2ihzQNqXYMdUPRUCoTqgk+26KYpExBfWHUupmlOPWrFkjnOvIerywPThFVci5jlLyKGpDESiq/3kUFPmj/44r0vhWk9DfRmlwVH9GdWEMwzDGAosjhmEYhmEYhmEYdqtjGIZhGIZhGIaRsDhiGIZhGIZhGIapjDi6e/eucFWiJnPk2EPOQKdOnVLtpyw9ysEm1xvaT245YWFhRc5BFq1kNUp9F8iClpyBqKldYajLOeU6k0sQWbsq1qgMwzAMwzAMwzBat/KmwlTqf9GzZ09h/0qFoyR8Ctuikoihng/Ut6NBgwZ4//330b9/f1HcqXT5JmFE9qA7d+4UxatTp07Fc889hxUrVoj9SUlJwgKUhNWCBQtw4cIF0VeChBQdVx7IFvXevXuwt7evVKdvhmEYhmEYhmEMAwrgkNEOmeaU2a6iItZ2b7/9dn7Xrl1L3Z+Xl5fv4eGR/+2336ruu3//fr6lpWX+33//LW6HhIQIW8+TJ0+qjtm2bVt+jRo1VPak8+bNE9aqivWo8ty+vr7lHmt4eHgRG1G+8IUvfOELX/jCF77whS/GfQkPDy9TQ1QocrRp0yYRBRo7dqzodq501qYGeEq3cLI6pYiPgqOjo+jAfvToUdEYj64pAkRd4RXoeFJwx48fF03p6Jju3bvDwsJCdQw9L3WCp+hV8QZ+RGZmprgUVodEeHi4SN9jGIZhGIZhGMY4SUpKEqU6lFVWFhUSR9evX8f8+fNFN3XqDH7y5Em8/PLLQsRQt24SRoS7u3uRx9FtZR9dF++ZYGZmBicnpyLHUEpe8XMo+0oSR9Tt++OPP37ofhJGLI4YhmEYhmEYhqnxiHKbChkyUB1P69at8cUXX6BVq1ai/oeiRlQXpG3eeecdJCYmqi4UMWIYhmEYhmEYhikvFRJH5EAXEBBQ5D5/f3/cvn1bbCudw6OiooocQ7eVfXQdHR1dZH9OTo5wsCt8TEnnKPwcxbG0tFRFiThaxDAMwzAMwzCMRsUROdWFhoYWue/KlSuoV6+e2KZUOBIvu3fvLpLfR7VEnTp1Erfp+v79+zh9+rTqmD179oioFNUmKcccOHBAONkpkLOdr69viSl1DMMwDMMwDMMwVaUGuTKU92CqMercubOo7Rk3bhxOnDgh0up+++03Yc9NkGnCV199VcTKm3oWFbbyHjhwoIgEUTqeYuVNBg2KlTelxZEQIjvvt99+GxcvXhRW3rNnzy63lTeJMjKDoHOVFUXKzc0tIsKY6sPc3BympqbaHgbDMAzDMAxj4CSVUxtUSBwRW7ZsEfU91N+IxA+ZMyhudQSd7sMPPxSCiSJEXbt2xbx589CkSRPVMZRCN3PmTGzevFm41I0ePVr0RrKzs1MdQ4JqxowZQpC5uLjgpZdeEkJJXS8AjZPMHWiMjPYg50KKNnIvKoZhGIZhGEZTaEwcGcoLQE1oSRiRc56NjQ1PzqsZ+tilpaWJ+jMSSFTPxjAMwzAMwzDaFEcVsvI2FCiVThFGzs7O2h6O0WJtbS2uSSDRe8EpdgzDMAzDMIzeGDIYCkqNEUWMGO2ivAdc98UwDMMwDMNoG6MURwqcSqd9+D1gGIZhGIZhdAWjFkcMwzAMwzAMwzAKLI4YhmEYrZGXl4/PtoRg9alwbQ+FYRiGYVgcGTs3b94UqW1BQUHaHgrDMEbIqVsJ+P3QDXy8KVgIJYZhGIbRJiyOGIZhGK1x8W6iuE7NysWdhHRtD4dhGIYxclgc6TFZWVnaHgLDMEyVCL6XpNq+HPlgm2EYhmG0AYsjpSFpVo5WLhXpwdujRw/MnDkTs2bNgouLC/r374+LFy9i4MCBsLOzg7u7OyZPnozY2FjVY7Zv346uXbuKRqvU02nIkCG4du2ahl5JhmGYihF8T0aOiMuRyVodC8MwDMMYZRPY4qRn5yLggx1aee6QT/rDxqL8b8PSpUvxwgsv4PDhw6KRba9evTBt2jTMnj0b6enpePvttzFu3Djs2bNHHJ+amorXXnsNzZs3R0pKCj744AOMHDlS1BiZmLA2ZhhGe2Tm5OJqdIrqdiiLI4ZhGEbLsDjSMxo3boxvvvlGbH/22Wdo1aoVvvjiC9X+P/74A15eXrhy5QqaNGmC0aNHF3k87Xd1dUVISAiaNWtW7eNnGIZRuBKZgpxCJgycVscwDMNoGxZHAKzNTUUER1vPXRHatGmj2j537hz27t0rUuqKQ6lzJI7CwsJEtOj48eMi3S4vL0/sv337NosjhmF0IqWusZsdwqJTcDMuDRnZubCq4O8iwzAMw6gLFkeAsLKuSGqbNrG1tVVtU5rc0KFD8fXXXz90nKenp7im/fXq1cPChQtRu3ZtIY5IFLGZA8MwumLG0NPPDTEpmbifli3S7JrVcdT20BiGYXSC3Lx8bDp3F118XOBmb6Xt4RgF+qEImBJp3bo11q5di/r168PM7OG3Mi4uDqGhoUIYdevWTdx36NAhLYyUYRim9MhR09oO8HW3x/Eb8cKUgcURwzCMZMXxW3h/YzDa1quFf6Z3Egv6jGbhinw9ZsaMGYiPj8eECRNw8uRJkUq3Y8cOTJ06Fbm5uahVq5ZwqPvtt99w9epVYdJA5gwMwzC6sBp6KSJZJY78POzFdijXHTEMw6hYd/auqmH2sevx2h6OUcDiSI+hNDlyrSMh1K9fPwQGBgqbb7LtJic6uqxcuRKnT58WqXSvvvoqvv32W20Pm2EYBjdiU4VTKNVdNnCxg5+ng7if7bwZhmEk4fFpOHv7vur23L1XtToeY4HT6vSIffv2lehet27dulIf06dPH+FMV5jCvZUoJa8ivZYYhmHUmVLn52kPU5Ma8FVFjlgcMQzDEJvP3xPXlHZ8LSYFh67GIij8Plp61dT20AwajhwxDMMw1U5IgRkDpdQRTdylOIpOzkR8KhvGMAzDbD4XIa6ndKmPEa3qiO05ezh6pGlYHDEMwzDVjuJU17S2NF+wszSDl5O12OZ+Rwyje9y9n47BPx/E4sM3tD0Uo+BqdDIuRSTBzKQGBjT1wAs9GoG8GHZdihL3M5qDxRHDMAxTrVAqb2GnOgVfd7nNqXUMo3ssO3ZLLGrM3nkFmTm52h6OwbOpIGrUvYkratlaoJGrHQYFyjYtXHukWVgcMQzDMNVKRGIGEtKyRa2Rkk5H+Hty3RHD6OqCxuZzsv4lKSMHey9Ha3tIRvN6D20hBRExo4ePuN56IQLXY1K0Nj5Dh8URwzAMo5WUusZudrAyN1Xdr5gysGMdw+gWZAJwJyFddXt9gb00o7nfSHL0tDQzQd8AD9X9AbUd0NvPDeSjNX/fNa2O0ZBhccQwDMNUK0pKHf1HXxil19GVqGTk5bGLJsPomjFAszryO7v3cgzup7FxiqbYVBA16u3vJuoxCzOjl49KoN5JSNPK+AwdFkcMwzCMlpzqpBmDQn1nW1iYmSAtK7fIKjXDMNqDFiq2XpCT9Vm9m4hFjKzcPJHaxWjm9d5SII6Gtaj90P7W3rXQuZEzcvLy8duB61oYoeHD4ohhGIbRklNd0ciRmakJfFztxPYldqxjGJ3g5M14RCVlwsHKDN2auGBkgaX0Bk6t0winbyfgXmKGiBj18HUr8ZiZPWX0aOXJcEQnZ1TzCA0fFkcMwzBMtUGpOGQJXFJandIUlmBTBobRrUakA5p5wNLMFMNb1hGW0idvJiA8ntO61I1ixNCvqXuRmszCdGrkjFbeNZGVk4dFB9laXd2wOGJKpH79+vjxxx9Vt2vUqIENGzZodUwMwxhOSp23kw0crMwf2q/UHbE4Yhjtk5Obh38vRIrtIc1lipeHo5VI6yI2BnH0SP2vt0xXHFpCSl3hOZkSPSKLda7/Ui8sjphyERERgYEDB5br2I8++ggtW7bU+JgYhjGclDoFXw95PzeCZRjtc+RaHOJTs+Bka6ESRMSIljK1bt3Zu8J2mlEPR6/HITYlC7VszNHVx6XMY3v5ucHf0wGpWblYfPhmtY3RGGBxZMBkZalvJcHDwwOWlpZqOx/DMMZJSc1fS4ockY1tRjY3mmQYXUjxGhToIWoCFWSKnQmux6Tiwl35nWaqzqYg+XoPDPSEeaHXu7To0YyejcT2kiM3kZKZUy1jNAZYHBG06pGVqp1LBVZcevTogZkzZ4qLo6MjXFxc8P7776tWbSgV7tNPP8WTTz4JBwcHPPfcc+L+Q4cOoVu3brC2toaXlxdefvllpKamqs4bHR2NoUOHiv0NGjTA8uXLH3ru4ml1d+7cwYQJE+Dk5ARbW1u0bdsWx48fx5IlS/Dxxx/j3Llz4jF0ofsYhmGKRo6KOtUpuNlboqaNOcjJ+2o0NzlkGG2RmZOL7cEypW5oQUqdgr2VOfo1lf13uOeR+l/vklzqSmJgM080dLVFYnq2SK9j1ENR83RjJTsN+KJ8H0S18797gIVtuQ9funQpnnnmGZw4cQKnTp0SAsjb2xvPPvus2P/dd9/hgw8+wIcffihuX7t2DQMGDMBnn32GP/74AzExMSqBtXjxYnHMlClTcO/ePezduxfm5uZCPJFgKo2UlBQ89thjqFOnDjZt2iSiSmfOnEFeXh7Gjx+PixcvYvv27di1a5c4noQcwzBMelYurhV0dS8tckQLKr7u9jh+I140g21Wh38/GEYbHLgSi+SMHLg7WKJdfaeH9o9sVVtElujy7iD/IpElpuLsD40p8/UuCVOTGnixhw/e+Occfj94A1M61y/VxIEpPyyO9AyK/MyePVtOIHx9ceHCBXFbEUe9evXC66+/rjp+2rRpmDhxImbNmiVuN27cGD///LMQN/Pnz8ft27exbds2IbbatWsnjlm0aBH8/f1LHcOKFSuEyDp58qSIHBE+PrIwkLCzs4OZmZkQTQzDMApUR0QRIRc7S7g5WJV6HOXRkzgK5bojhtF6Sh0ZMZiY1Hhof7fGrqIWiWpkDl6NRc9SbKeZ8rH5fITq9SbRU16Gt6yNH3ddEb3hVp0Mx1Od62twlMYBiyPC3EZGcLT13BWgY8eOQhgpdOrUCd9//z1yc2VuPqW3FYbS286fP18kVY7S8CjKc+PGDVy5ckUImTZt2qj2+/n5oWbNmqWOISgoCK1atVIJI4ZhGHWYMSj4FtQdUeSIYZjqJy0rBztDosp0TaOamKHNPbH06C3R84jFUdVe712PeL1Lg96H5x9rhPc3XMSv+69hQntv0UybqTwsjggSGxVIbdNlqP6neArc888/L1LlikPpeCSOKgrVJjEMw1RWHJXU36gkccR23gyjHfZcjkZ6di68nKzRom7pqa0jW9cV4mhHcKQwBKDGpUzF2XVJvt7U4qCs17s0xrapi192h4nmsSRUx7Xz0sg4jQWWlnoGmR4U5tixYyJVztS05BzT1q1bIyQkRKS9Fb9YWFiIKFFOTg5Onz6tekxoaCju379f6hiaN28uokfx8fEl7qfzKpEshmEYhZBHONUpNHGX4ig6OVPYCDMMo52UOjJiKJytUhyayDdwsUVGdh7+KzATYCrvUje0hWeZr3dpUJ3Rs90aiu15+66KfklM5WFxpGdQjdBrr70mBMzff/+NX375Ba+88kqpx7/99ts4cuSIMGAgQRMWFoaNGzeK2wTVLZFhA0WXSHiRSKI6pbKiQ+RSR/VEI0aMwOHDh3H9+nWsXbsWR48eVbnmUcoePV9sbCwyMzM18EowDKNP0H/WSppcaU51CrT6TCvWBPc7YpjqJSkjG3tDY8qV4kUTeaXnEbvWVY7EtGzsvyJNsIa1kK9lZXiig7dw+rwZl4atBY1kmcrB4kjPIJvu9PR0tG/fHjNmzBDCSLHsLi3Ks3//fpE+R3beVCtEbna1az/4wSPXOrpNJg2jRo0S53NzKz13mCJD//33nzhm0KBBCAwMxFdffaWKXo0ePVoIrp49e8LV1VWIOIZhjJtrManIzMkTwqee06NrLf0KmsFyah3DVC87g6OQlZMHHzc7Vd+xshjZSk7oD1+NRVRSRjWM0LCglMTs3Hw0cbdTpRRXBltLMzzdpYHYnrf3GvLI/YapFJwcqmeQ1faPP/4onOaKc/NmyR2SyYWOxExpUBRoy5YtRe6bPHlykdvFO2DXq1cPa9asKfF81Cy2tH0Mwxh381d/T/sSna+KQ5MyKghnccQw1cuW8+VLqVPwdrZBm3q1cPpWgkjHm1aQ3sWUj80Fr3d5exuVxVOd6uO3A9cRGpWMXZeiVL2omIrBkSOGYRhG681fi8OOdQxT/SSkZuFgWKzYHtLCs9yPG1EQPVp3hlPrKkJMcqaIuFXGpa4kHG3MMblTPbE9d+/Vhxa2mfLB4ohhGIaptsjRo5zqFJR0nitRyZwewjDVxPbgSOTk5QvTlEauduV+3JBAT5ib1kBIRBJHeyvAtosRovcbGVvUc1aPa/IzXRvAytwE5+4k4lCB8GIqBosjPWLfvn0ipY5hGEafoNXLkHL2OFKo72wrenWkZeUiPCFNwyNkGKZ449eKUMvWAj0K+hxtCOLoUcVd6qoeNVKgJtuPt/MW23P2XFXbeY0JFkcMwzCMRqHO7UkZOWJlubFb+QqOzUxN4FOwcs2pdQyjeaKTMnD0epzYHtK8/Cl1xY0ZNp69y9HecnD3fjpO3UoQrTYrKkYfxfOPNRS/t8dvxOPUzZLbrjClY9TiKC+PfeC1Db8HDGM89UbUv6gindv9PLkZLMNUF/9eiACVqLTyrgmvcjhKFqeXnxvsLc1EI1KalDNls6UgSte+vhM8HK3Uem5PR2uMbl1XbM/Zy9GjimKUbnVkRW1iYoJ79+4Jq2m6XZmmW0zV0myysrIQExMj3gt6DxiGMe7mr6XVHbE4YhjNs/l8hMqlrjJQI9JBgZ5YdSocG87eRadGzmoeoWG61Kkzpa4w0x9rhNWnwrEvNAYX7yaiWZ3ymeEwRiqOaDLeoEEDRERECIHEaA8bGxt4e3uL94RhGMOkok51Cr4FvY64ESzDaJY7CWnCipvWiQdXIqVOYWTrOkIcURTq4+FNhWBiHuZ6TAou3k2CqUkNISg1QX0XWyG8NgbdE8518ye10cjzGCJGKY4IilTQpDwnJwe5ubnaHo5RQk1jzczMOGrHMEYjjioXOboRm4qM7FyeaDGMhthaEDXq0MAJ7g6VT/GiFLHajlYitW7P5WiNTfz1nc3n5Ovd1ccFTraay5x5sYePEEfkQng1Ohk+5az5NHaMVhwRNCmnpqp0YRiGYdRPXEomIpMyxIq0v2fFxJGbvSVq2pjjflo2rkancFoIw+h4ihc1eB7eqg7m77smeh6xOCq5rGDTubtqa/z6qH5x/Zu6Y0dwFObtvYYfxrfU6PMZCpzLxDAMw2g8atTA2Ra2lmYVXsBSokfsWMcwmk/xGtis6mJGca3bFxqN+NQsNYzQsKBeUNdiUoU5Tb+m7hp/vpk9G4vrjefu4XYct0UoDyyOGIZhGI2Lo/I2fy2OX0HdUSjXHTGMRthyXr0pXuRKSSm01Ex26wV5bubhlLpevm6wt9J85lJgXUd0b+KK3Lx8zN9/TePPZwiwOGIYhmE0RrDKqc6x0mkhBEeOGEZTKV7qd01TokfkWscUfb2VRruacqkriZk9fcT12tN3EJmYUW3Pq6+wOGIYhmE0RkglzRiKiyO282YY9RMalSzq+SxM1ZviRRN/kxoQDni34lLVdl5958zt+6L5q62FqegLVV20b+AkzDKycvPw24Hr1fa8+gqLI4ZhGEYjpGbm4EbBxKiy4ohSdIjo5EyuX2AYNbOlIMWrh68rHNSY4kWOd118XMT2hrPcMkVBiRr1DXCHtUX1um/O6CWjRytO3BJGOUzpsDhiGIZhNMKliCTk5wMeDlZwtrOs1DnsLM3g7WQjtrnfEcOoOcVLg41IVal1QXfFcxk7VPOj1HcNa1l9KXUK3Ru7ILCOIzKy8/DH4RvV/vwGK44++ugj4R5U+OLn56fan5GRgRkzZsDZ2Rl2dnYYPXo0oqKiipzj9u3bGDx4sGj+6ebmhjfffFP0GirMvn370Lp1a1haWsLHxwdLliyp6t/JMAzD6JkZgwKn1jGM+rlwNxG34tJgbW6K3v7qT/Hq39RDnJv6lAWF34exc+x6HGJTMuFobY6uPq7V/vw0Z59RUHv055FbSEzPrvYxGGzkqGnTpoiIiFBdDh06pNr36quvYvPmzfjnn3+wf/9+3Lt3D6NGjVLtp2arJIyysrJw5MgRLF26VAifDz74QHXMjRs3xDE9e/ZEUFAQZs2ahWnTpmHHjh3q+HsZhmGYajdjqJo4Uuy8WRwxjPpTvEgY2Viov+0lWfcrdUxszPDg9R4U6CFsvLVBvwB3NHG3Q3JmDv46elMrY9AHKvzumJmZwcPDQ3VxcZE5pYmJiVi0aBF++OEH9OrVC23atMHixYuFCDp27Jg45r///kNISAiWLVuGli1bYuDAgfj0008xd+5cIZiIBQsWoEGDBvj+++/h7++PmTNnYsyYMZg9e7a6/3aGYRimGiJHVRVH7FjHMOolr1CKlyZd05TUus3nI5CdmwdjJSsnD9suRortoc2rP6WucJPeF3vI6NGiQzeQllU0c4uppDgKCwtD7dq10bBhQ0ycOFGkyRGnT59GdnY2+vTpozqWUu68vb1x9OhRcZuuAwMD4e7+wBGlf//+SEpKQnBwsOqYwudQjlHOURqZmZniPIUvDMMwjPYmA1eikh9t452ZDCwbDez88JGRIzofTeoYhqkap28nICIxA/aWZnisieZSvKh3koudhTBTORgWA2OF/nZKY3O1t0SHhs5aHcuQ5p6ijjMhLRsrjss5PFMFcdShQweRBrd9+3bMnz9fpMB169YNycnJiIyMhIWFBWrWrFnkMSSEaB9B14WFkbJf2VfWMSR20tPTSx3bl19+CUdHR9XFy8urIn8awzAMo0bCopORnZsPBysz1K1lXfqBR+cCV3cBh38EIi+WeEh9Z1uRhpKWlYvwBO7wzjDqSvHq19QDVuaac00zMzVRRabWnTHe1Dqll9TgQE+Ykse5FqH35IUejcT2woPXkZmTq9Xx6L04ojS4sWPHonnz5iKa8++//+L+/ftYvXo1tM0777wjUvuUS3h4uLaHxDAMY7QUNmOgQuASSYsHjsx5cPvwT6X+Z97YzU5sc2odw1SNnNw8/HtBSanz1PjzKal1O0OikJxhfCYA6Vm54m/XlktdSYxqXUe4iEYlZWLN6TvaHo7OUaWKMIoSNWnSBFevXhX1R1Q3RGKpMORWR/sIui7uXqfcftQxDg4OsLYuffWRnO3omMIXhmEYRtvNX8tIqaNoUVYy4FBX3r64FkgouUiYHesYRj0cux6P2JQs1LIxV/Ui0iRkH93I1RaZOXnYXlB3Y0zsvhwlot4UQW/lVTS7qlzkZAIX1gD31ZcCZ2lmiue6NxTbC/ZfE4KZUZM4SklJwbVr1+Dp6SkMGMzNzbF7927V/tDQUFGT1KlTJ3Gbri9cuIDo6GjVMTt37hRCJiAgQHVM4XMoxyjnYBiGYQzAqS45Ejj+m9we/B3QqDeQnwsc+aXEw9mxjmHUm1I3MNAT5qYVnAZGhQBZFUttpchx4Z5Hxvp6U3phqVH00sjJAlY/Cax9BpjXGTivvkytCe294WxrgfD4dFXaHyOp0LfijTfeEBbdN2/eFC50I0eOhKmpKSZMmCDqfJ555hm89tpr2Lt3rzBomDp1qhA1HTt2FI/v16+fEEGTJ0/GuXPnhD33e++9J3ojUeSHmD59Oq5fv4633noLly9fxrx580TaHtmEMwzDMLoPmSZciniEGcPBH4CcdKBOW6DJAKBrwW/82WVAyoMFNAVfDymyLnEjWIapomtaROVc0/Z/C8zvBPzaXS5uVIDhLaU4OnItDhGJpdePGxpJGdnYGxpTudc7NxtYMxW4sl3epij7umeBdc9LI5sqYm1hime6NRDb8/ZdY7ObyoqjO3fuCCHk6+uLcePGiWavZNPt6iqdTshue8iQIaL5a/fu3UWK3Lp161SPJyG1ZcsWcU2iadKkSXjyySfxySefqI4hG++tW7eKaFGLFi2Epffvv/8uapwYhmEY3ed2fBpSMnNgaWYi0mke4n44cHqx3O79Pi0tA/W7SqGUkwEcX1Bq5OhmbCoysrmAmGEq65qWlJEDN3tLtG/gVP4HnlgI7P1MbseFAUuGVEggeTnZoF39WsjPBzYFGU+U4r/gKCFIfdzs4O8pf8PKRW4OsHYacHkLYGoJTFwL9PgfUMMEOL8SWNANuHu6yuOb3LGeMM25Gp2CHcHGl/KoFnG0cuVK0diVbLNJKNHtRo2k4wVhZWUlehbFx8cjNTVVCCOllkihXr16wsghLS0NMTEx+O6770TvpML06NEDZ8+eFc9DaXtTpkypyDAZhmEYHTBjIEFDZgoPsf9rIDcLqN8NaNhD3kcCSYkenfgdyCgaIaLJHNVI0OIm/UfOMEzlU7wGN6+Aaxqlcv37htxu/xzg6FUpgTSylawtXG9EDWGVdDWKGpU7pS4vF9gwHQjZAJhaAI8vBxr3AXq8DUz5V77+CTeARf2AQz9SqL7S47O3MseUzvXF9py9V5FP6pWpWs0RwzAMw5RWbxRQUkpd3DUgaIXc7v1B0X2+gwAXXyAz8UFkqQCaWHAzWIapPBRxVVzTyt34NXQ7sH663G7/PDDwG+CpzYUE0uByCySysbYwNRHf30sRhp8eG5eSicNXYyvmCkhCZ+NM4MI/gIkZMHYp0Ljvg/31OgHTDwIBI4C8HGDXh8CykRVOcyzM1C4NYGNhKha19hWkABo7LI4YhmEYjUSOSjRj2PuFNF5o3B/wal90n4kJ0HXWg/5H2RlFdvsV1B2Fct0Rw1SYvZejkZqVizo1y+madvMw8M9T8vvafDww4CsZ4XVqAEzZUiCQrkqBlCTrmMrC0cYcPf1kGcYGI4ge/XsxErl5+WhWxwENXWUrgkcKoy2vAOdWADVMgTF/AH6DHj7OuhYwdgkw7BfA3Aa4vg+Y31kK2UpQy9YCEzt4i22OHklYHDEMwzDVI46igqVdN9HrvZIf3GyMtPZOiQLO/V1kF0eOGKbybD5fAde0e0HA34/LGsAmA4Hhc+XihUKt+kUF0tIh5RJIimvdxqB7QjgYQwrjsPJE6UiQUOrimT9lXdHohUDA8NKPp/ev9ZPAc/sBj0AgLQ74ezyw7e2HFpXKw7PdGopG26dvJQird2OHxRHDMAyjNqKTMhCbkgkqZ1AiPSr2fE6zAJkS4tm85BOYWQCdZz5oCkv59wWwOGKYykEGKbsvSRfIIc0fkeIVGwYsGw1kJgH1ugJjFwOm5g8fpxJI3uUWSD393IQBQGRSBo5fj4OhQo58J29KkTH4US51JIy2vwOcWkSqBxixAGg2unxP5NoEmLYb6PiivE1mNr/3AWJCKzReNwcrjGsra8Lm7r0KY4fFEcMwDKP2qFEjVzthFavizmkgdKtcFe35v7JPQiuilDpCRcchG1V3N3GX4igmORPxqVka+gsYxvDYFRIlmrA2dLEtvfeY4iT55wggLRbwbAFM+Bswty79+OIC6REpdtR8VBEL6ww4tW7r+Qihecihj9IYS4UO2vk+cHy+vD18DtBifMWezMwSGPAl8MQ/gI0LEHUB+PUx4PQSef5y8nz3RsKk49DVWASF34cxw+KIYRiG0XzzV8UGmGoXXH3LPomFLdChoAj80GzVf/B2lmbwdrIR25e57ohhKpziNaSslLqUGOCvEUDSHcC5MTBpHWBVhpBSqFXvgUCKv1YgkO49MrVu+8VIpGflGrZLXVkpdfS7tvuTB42vh/wItJpU+Sdt0g944QjQsKfsIbf5FdlANj2h3HbrIwr6Uc3ZY9zRIxZHDMMwjAbqjRyLFnZf2yPdlx57u3wnIstgc1sg8rx8bLHUulBOrWOYcnE/LQsHwpRGpKWk1GUkAstGyegP1fw9uQGwdSn/kygCqaYikIaUKpDa1quFurWsRarfrkvSPc+QoF5s5+8kiijMoMAyUhippcGhH+T2oO+AtlOr/uT27lLU9v0UMDEHLm0C5ncFbh0p18Nf7NlIlDPR+2LMC1AsjhiGYRjNmTHQ6uieTx+ky5HTVXmwcQLaTHkQPSrWDJbFEcOUD2rumZ2bL747jQtSU4uQnQ78PUEuRFBaFgkjR1l/UiFIID31aIFkYlJDFaEwRNc6JUrXuZEzXOwsSz7owHfAvi/ldv8vgfbPqm8AZJzR5WXgmf8Ap4YyEkjRvL1fyuayZUDp0IOaSUE3d+81GCssjhiGYRi1kJSRjdvxaWI7QBFHV3cDt48CZlZA9zcrdsJOM+Tq582DwJ1TRSJHl1gcMUy52HwuovQUr9xs4J8pwK3DgKUDMHkd4NK48k8mIkhbCwmkklPsRrSSY9l/JUb0AzJUV8ASIaMZZcGo7ydApwIzBXVTpzXw/AGgxRNAfh6w/yv5fty//cjoEbH1/D3ciE2FMcLiiGEYhlELIQVRIypArmljUTRq1G4a4FDOxpMKjnVkjVKh6JESOQqLSkaegVsBM0xVIfOSI9cKGpEWd02jvjobXgSubJeLF0+skiYMVYWEkUogXZcT8sSiESIfN3sE1nFETl4+tpx/tAW4vkCpaFeiUkSz2/5NPR4+4Nh8YOcHD9oZdHlFswOytAdGzgdG/Q5Y2APhx2SaXfD6Uh/StLYjevm5gX5e5+8zztojFkcMwzCMWlPqVFGjS5uBiCDAwg7o+mrlTkrpIWRve3mLsKet72wr+nGkZeUiPEFGqRiGKZltFyPEJLeFV014O0szkwf20W8DF1bLWsBxfwL1OqvviVUCqZ4USGTzXUwgKcYM6w0otU5JqXvM1xWO1sXsz08sBLb/n9ym2suKRtKrQvOxwPSDQJ22QGaijBZunAlklRwZmtHTR1yvO3MXd++nw9hgccQwDMOo36mO+hPtpb5GADq+ULHi7sKQs53fYLl9+CeYmZqgsZvsNs/9jhimfJP1h4wYqN7lxG9y4WHkr0CT/up/ciGQtjwQSMUiSJR2RqYFZBttCOlb+fn5qhTGhxq/kq02NXklaKGoxzvVP0Cq93x6O9Dtdfm+n/1LWn5HnH/o0Db1aqFTQ2cR2fttv/HVHrE4YhiGYdSaViec6i6uBWIuA1aOQKeCpq6VRYk6nV8FJN5hxzqGKQf37lMj0gThPjakcErd0XnSKY0Y/B0QOEZzgygcQaK+ZYUEkqu9Jbr6uBhM9OjcnURRc2ltbore/m4PdpxdDmyeJbfpt7D3hxBvijagZr69PwCe2gTYewJxYcDvveVnolhPpJd6yejRypPhIj3TmGBxxDAMw1SZjOxchEWniO2m7tbA3i/kjs4vA9Y1q3byum2B+t2AvBzg6Fx2rGOYcjYiJdrVd4KHo5W8M2gFsOOdBzUvVAuoaWp6lSCQ7hRJrSPXOoq86DObgmSUrm+AO2wszOSd51cDG2dQXAlo/zzQ7zPtCaPCNOgOTD8M+A4CcrPkZ2LFONnrqoBOjZzRyrumaB78+6HrMCZYHDEMwzBV5kpUMnLz8lHLxhyeN9bJSZCt64NmrlVFiR6dXoKmtWTjyEtG3IeDYR7FluKuaZe2yDoTJYLRrSDNqzpQBFKt+gUCiWqQ7qBfUxISpiLicub2fegr9Nv30Ot9cR2w/nkpjNo+DQz8WjeEkYKtM/D4CtljydQSCPsPmN9ZOoxS4l2NGphZUHu07Ogt0S/LWGBxxDAMw6jNjKGlpzVqHPhG3tn1NcBS1gdVmUa9pJNWdhpa3FutarZIESuGYYpyKy5VpHlRTc/AZh7A9f3AmqlAfi7QcpJ2IhgkkKgPkkogDYZNeiQGFLi66XPPoxM34hGdnAkHKzN0b+IizWjWTpMW2q0mA4O+1y1hpEBjoh5Lz+0FXP2B1GjZDPi/94CcLOFa5+/pgNSsXCw+fBPGAosjhmEYRm31Rk+Y7gaS7gIOdeRqqTr/Ey+IHtkG/Q5P61zhwnW1IJWPYZgHKPbYohFp4kVg5RMyfcpvCDD0J+1N1ItEkG4KgTS+SQ1Vf6CsnDzoc2+jAc08YHntP+CfAiHaYgIw9GfZmFWXcW8qBVLbZ+TtI78Ai/qiRvx1zCjoe7TkyE2kZJbdRNZQ0PF3i2EYhtEXpzprZKBb1J/yDrKpNS+oc1AX/sNEx/ca6QmYbn9I3MWOdQxTukvdxAbpwLIxQFYK0OAxYPQiwLSgHkZbONYtIpDaH3gSzeyScD8tWzSF1Teyc/Ow7YIUo0+5hAGrnwTysoFmY4Dhc3VfGCmYWwNDfgDGLwesa8k2DAu6YVDuXjR0sUFiejaWHbsFY0BP3jGGYRhGl/PtL0UkY6rpDlhlxgG1GgCtJqn/iUxMVU0TR6SvhzlyEMp1RwzzUP0fLRrUN41FvzPTgfR4oE4b4PHl6l+wqLJAaoAaCTfxl+mnqI1YvUytO3Q1Fglp2RhkcxkBB1+UEbqA4dIinX6z9A3/IdKsoV5XIDsVJhtfxBKH32CPNPx+8IZRpDKzOGIYhmGqBPUoMc9OwvNmW+Qd1MODLGM1AaWp2HnAMTsaw00Pc+SIYYqx5dw9uCARq6y/hklKBODqB0xcA1hKl0edQQgkqkFqgFqZd7HS4lNcvBQsIhT6xOage+hoEoIf879GjdxMwHewbkToqoJjHWn3TY6GNUzhfe9fbLd+F16pF7HqZDgMHRZHDMMwTJVT6p4x+xeONVLlREyTfVPMLIFOL4rN6aabERohG88yDCMbke45F4Y/Lb6Ce85d2Wdo8nrAxgk6SUEEKb9WA3ibxOAvk49x4OQZ6AsURYkN2Yc/zL+FRX4m0Lg/MHax5haHqhMTU5keTY1ja3qjTn4U/rH4GOm7v0ZWln4J2IrC4ohhGIapEjdu3cIzptvkjZ7/03wqSZupyLdyhI/JPbRMO4L4VOOxmGWYsgi5FYmPkj9GgMkt5Nm6AZM3AA6FGsDqIo51UGPKViRa1RUCqf3+J4H7t6EPnD28A/PwJWxqZCK/UW9g3J9yAceQ8GoPTD+E3IBRMKuRh+m5K5Dw6yAgSda1GSIsjhiGYZgq0ThsEexqZCDewV+aJmgaKwfUaPes2HzRbBMuc/SIYYT1stX6KWhrcgVpJnYwoYiRs3Qa03kc6yBt4ibcyHOHe24kcv4YrPsC6e5ptDwwTfz23XRoixq6VNOlbqwcYTr2D+zz/wip+ZZwjzuBfOqJdHkrDBEWRwzDMEylyU+6h94pG8V2Yqf/qz6L4A7TkVXDAi1NriHx0t7qeU6G0VXycpG//nk0SjyG9HwLnO/+G+DRDPqEp1cjfOPxnRBIZkm3hc23zgqkiHPI/3MkrPNScTzPD6mjlkm3N0OmRg20G/ESJph8gwt59YVrqLCI3/o6kJ0OQ4LFEcMwDFNp0nZ9BStk41SeL2q3HVJ9T2znimD34WKzYejC6nteRvvEXQN+7Q6smgTcC9L2aLRPfr6YoNYIXoesfFO8gjfQsssA6COPtW2Jx7Pex10TTymMdFEgRV4E/hyOGpmJOJnXBB/bf4SAerKRraFja2mG3l26YFTWJ1hjOULeefJ3YGEvICoEhgKLI4ZhGKZyJNyE9YXlYnOVw1OwNK9ed6b4Fs8hJ98EvikneJJsLNBq9YpxYuUelzYDvz0GrBgP3DkNo2X3J8DpxchHDbyaPQN2Af1hZa6HFtIABgZ6IsHMBaPS3kWmQ/0HAilBR/rrRF8Wwog+h9cs/DA16y30bdkINbTVVFcLTOlcH5aWVngjcRzOdF8EUG1bdAiwsKcUSiTW9RwWRwzDMEzl2Pc1TPJzcCA3EHneXav96es1CsDmvE5iO//Qj9X+/Ew1k5sDrHkaiLsKONQFAscBNUyAK9uB33sBy0YD4SdgVBz+CTj0g9j83OR5bM3riKEtdNyAoQwcrc3Rx98NUXDCrw1+ApwaSYG0dIj2BVJsGLB0KJAWixz3FhiT8gZSYKPXr3dlcLQxx6SO9cT2x5c8kf/CYcCnD5CTIVPsKKKbFg99hsURwzAMU3FiQoHzK8Xm9zlj0bS2Q7UPob6zDRbly9Q6XNoo060Yw2XH/4BrewBzG2DC38DohcDMU0DLiaIXC67uAhb1lSv7t47A4Dm9FNj5gdi82eot/J7WHTVtzNHFxwX6zIiWdcT1spAc5D65+YFAWqJFgUS/LSSMUqMB90BsaDYXCXk2CPB0gI+bHYyNad0awMrcBOfC7+NwhAnwxD9A/y8AE3Pg8hZgfhfgxkHoKyyOGIZhmIqz70sgPw8HTdrhXL4PArQgjsxMTZDvFoDdua1QIz8POPJztY+BqSZO/QGc+FVuj/wV8Gwut8mNbcQ84KXTQKvJgIkZcH0fsHignEzfOGAQaT4PEbwB2DJLbneZhV9zpUvkwGYesDDT76ldD183IfKikzNxJMZCNoolgZSoJYGUcBNYOgxIjgDcAoAnN2LtpVSxy9iiRgoudpZ4vJ232P5lTxhgYgJ0mgE8uxtwbgwk35NiklI+c/WvJ5J+f4MYhmGY6ifiPBC8XtQ4fJ4+WtylDXFE+HrYY37OUHkjaAWQHKmVcTAahATOv2/K7V7vAQHDEBqZjOSMQpMupwbA8DnAS2dEHyyxgn3zoJygLR4EXNtrOCKJomdrp4nFCbR+Ctk9P8C2ixFi19Dm+j9ZJ3E3pLmn2F5/9q7s0zRlK+DsU/0C6X44sGQokHQHcGkihFFUri2O3YgTu5VxGiPPP9YQ5qY1cPxGPE7dLEij82wBPL9fLlQgHzj4vVyoIIGpR7A4YhiGYSrG3s/FVWy9wbic7w1vJxs4WGmnI7yfhz1O5fvhqlUgkJsFHJunlXEwGkxnWv0kkJcDNBsDdHtDpPIM+OkARsw9jJTMnKLH16oHDP0ReCUIoF5YphbA7SPAXyOARf2AsF36LZKopmrlRCAvGwgYAQyZjUPX4nA/LVus5ndo6AxDYGQrmVq342Ik0rJyAAdP4Kkt1SuQqMkp1TrR81Hk6qnNgJ0btp6PEB+h1t414eVkA2PF09Eao1vXFdtz9l59sMPCVi5UjFkMWDoCd05K05S8POgLLI4YhmGY8hN+UhbA1zDFHs9nxF3aqDdS8PWQz72ohmIr+weQfl9r42HUSEYi8PcE6VBXu7WccNWogc3n7onJ6bWYVLy99jzySxI7jnWBwd8Br5wDOrwAmFkBd04Ay0dL2+HQ7fonkqKCgeVjgew0oFEvYNRCwMRUvB7E4EAPmJoYhmtaa+9a8HKyRmpWLnaGRMk7HxJIgzUXkaAItBBgN4Fa9aUwspd23ZsKXu9hRppSV5jpjzUCfeT2hcbg4t1izbibjQKmHwS8OwODvpOpd3qC/oyUYRiG0T57PpHXLSfgyP1aWhdH/h724nrVfT/kufoDWcnAqUVaGw+jJvJypTNdbChgX1saMJhbCyG081LBZBkQq/hLjpQxQaaUrIFfAa+cBzrNBMysgXtngL/Hy15Jl7box4p2/A3gr5FAxn2gbntg/DLAzAIZ2bn4LzjK4OpfyBp7ZIExg0itUyCBpEqxC38gYNRJSrRMx4y/Bjh6S2HkKMcSHp+GoPD7QhAMMuKUOoX6Lraqz93cwtGjwpHcqf8CDbpBn2BxxDAMw5SP6/tl/QfVczz2NoLvJYm7m9Z21NqQXO0tUcvGHHn5NXC32XR557H5Btex3ej4733pPkdiZsIK1ar9tZgU3IpLg4WpCd7o10Tc9/nWSzh9K6Hs89m7A/0/B2ZdEAYGMLcFIs8DqyYCv3aTBge6KpKSIqQDX0oU4NYUmLhapi6RL0pojEgtrO1oJaIthsSIgtS6g2GxiEnOfLCDPgtCIDV+IJBIPKqD1Dj5WsdeARzqAFM2AzWl8UDhqFGnRs5ws7dSz3PqOS/28BHX24MjcTU6+eED9LAHFIsjhmEY5tFQCtKeT+V226lIt6mD6zEpWo8c0QozmTIQJ2x6yIlMagxwdpnWxsRUkTN/Asfmyu2R84HarVS7doZEqyanM3r6YHBzT+Tk5WPmijOISyk0gS4NO1eg78dSJHV7A7CwB6IuAv88BczvDFxcK6NWugL1i1k2Crh/C6jVAJi8DrB+III2n5eT9SEtasPEQFLqFBq62qGFV03k5uWrUgeLCqQtDwSSiPTcqPpr/ddw2dDUzkNGjCilrhDKOAzB+EJd+HrYo1+Au/gvYt5ew2inwOKIYRiGeTRh/8nCWlrJ7/Y6LkcmIS9fWrq6OWh3BdWvoO7oUlQa0PlleSfZelPTUEa/uHkY2PKa3O7xDtB0ZJHduwpS6voEuAth/PXo5mjoaouIxAzMWhUkJtLlwtYZ6P0+MOu8iIKKwvGYSzKVb15H4Pxq7X9+MlOAFeMeTNaf3KCKoBGpmTnYXfB6GOpkfWRL+XdtCCqUWldcIJGLXFUjSFSnSGmLkRcAW7cC4dWoyCFhUcm4HJksHNoGNHvwPjDAzF4yerTx3D3cjkuDvsPiiGEYhikbSjdSokbtnxWTkgcpddqLGikokaPQqGTZENTGRTaNDF6v7aExFYFqR1ZPfuDE1v2tIrtjUzJx5rZMn+vj7yau7SzNsGBSG1ibm4r0q592h1XsOW2cgJ7/kyKp57uAVU2ZUrXuWWBue2kPrw2RlJMJrJokFyQoUkTCqFgUg4RiRnaeaIbcrI72v4eagCJiZDJx/k4irkbLSPVDAokiPCSQyG67MgIpIwlYNhqICJK/HeJ8jR86TIkadW/sipo2FpX+mwyR5nVroltjF7E4seCA/kePWBwxDMMwZXNpo1xRpRSkrq+Ku3RJHJGdN0GrurCwATq+IHccmq1/jmTGCk1QVzwOpMUBni2BEfMfcrfaczlavJ0kBMhGWKGJuz2+HBWoaki5L1Sm3lUI65rAY2/JdLveHwDWTrIgf8MLwJw2MtUvJwvVAokx6mN0fa+sjZq4BnDzf+iwzecKehu1qC2iaIYIRaYfa+IqtjeWFD1SCaQtxQTS9fJH58gB8O6pAhG6EXDze+gwMgJRudQVRLOYoszsKaNHa07dQWRiBvQZFkcMwzBM6VD9xd4v5DZ1QKeVdgAh9xK1bsZQeHJMUNF2fGoW0G6aFHLRwUDYTm0PjynPZ4zEAKW1UfoYOdORyC3GrgJL5z7+7iUW70/q6C3EE6XX3b1fSUMOKweRNipEUt9PZCSBIlqbXgJ+aQOc+kNGdTQF/QFbXgEubZI9mh5fDtRt+9BhiWnZ2H8l2uBc6soyZiDXurzS0ibJcKOIQBr6aIGUlSrTFsOPAVaOwOQNgEezEg+9eDcJN+PSYGVuUuLnj4HosdWufi1k5eZh4cFyilMdhcURwzAMUzrnV8k0I1pVJXFEGT+5eTJKoyORI1tLM9GIlqBaKBEFaDv1QfSI0W12fQSE7ZC9iB5fIe23i0GW1ZQ2R5Q2OX1/SACa13UUDVFfXH4GmTlVMFawtAO6vCLT7fp9LutQqLfOlleBn1sBJxYC2RnqF0b/vSfNRGqYAKMXAY16lnjojpBIZOfmw9fdXrU4YKj09XcX6ZN3EtJxuiCtsmyB5PvoCBK5WVIPrVuHAUsHYPJ6oHbLUk+96ZyMWvX2dxe/N0zJkEkKseL4bblQpaewOGIYhmFKhtKI9n0pt8n+mFbVhZ1yKjJz8sSERRElulJ3dDmiwEq244ty5f32EeD2Me0Ojimds8uleQYxfC5Qt02Jhx25Fov07Fx4OlqVKsgtzUwx94nWcLQ2x7nw+8Liu8qQZXbnmVIkDfgasPcEku4C/74B/NwSOLZAfbbxh34Ajs6R20N/BgKGlXqoyjWtheH32rG2MFUZIBTpeVSqQNpcIJDuliyQSNSunAjc2A9Y2AGT1gJ1Sv7cERSt2nJepjBy49eyoRTIwDqO4rv6xyE12atrARZHDMMwTMmc/VMaG9i5A+2fU90dXJBSF+DpoDP2wUrdUWhBREs0i2wxQW5z9Eg3IdG6ZZbc7v4mEDim1EMVC2+KGpVVX+PlZIMfx8sIwJ9Hb5Vep1JRzK2BjtOBl4OAQd/JHjjJEcD2t4EfmwNH5sg0rcpychGwu6DBMkWqWk8u9VCyLD9yLU5sDzFQl7rijCxIraOmv4+MCJJAEi52hQRS3LUHCz6rnwSu7QbMbYCJ/wBe7cs83albCcIN0d7STFX/xJQMfTdn9JQuf0uP3kRSRjb0ERZHDMMwzMPQaviB7+S26AfzIEKkmDEE6EBKXXE778vkWKdAaVGoAVzZDkQFa29wzMOQ6KbV+9wswH8o0ON/Za7cF7bwfhQ9/dzwUoG18P+tvSAsmNWGuZV0bHz5LDDkR8CR+mpFA/+9K0XSoR9lkX9FuLAG2Pr6g+8aRarKYNvFSOEKRimE9V1kM1hDp2NDZ7g7WCIxPRt7L8c8+gF2bkUFEvVBirkCrJlakMJpDTyxGqjX+ZGnUqJ0/Zt5wMrcVB1/jkHTL8ADjd3skJyRg7+O3oI+wuKIYRiGKXklm1bGHb2ANk8V2aVEjnSh3qh4Wh1NhFVF29SnJGC43D78kxZHxxSBxAPVe6TFAh6BwMhfH3KmK8z5u4nCbMPWwhQdG0pDkEcxq08TdPFxFuk905edFj2B1IqZpaxre/kMMGyOtNmmv2fXh8CPgXJhgRz4HsWV/4D1z1PBkTQS6fXeIx9ijI1Iyc57eEsZPdrwqNS64gLJ1U8KpPmdgMtbAFNLYMIKoEG3R56C6iv/vfDAFZB5NJRNoNQe/X7wOtKy9K/fHIsjhmEYpiiZybL+gSB7Y5oIFrK0DVHZeGvfqU6Ber1YmJkgLSsX4QmFmhAWWI+L1fkE/VzFNLieWeueA6IuSpODCStlXU8ZKC51j/m6irqi8k6mf3q8FTwcrESN3P+tuyA+u2rH1FymwM08Je3HnRoB6fGyLxiJpH1fywajJXHrqEzxyssBAscCA7+lvKQyn44skk/cjBfbg5sbfr1RSal1ZOlObn3lFkhUg0QCiV5nxQGwUa9yPZzSF+NSs+Bka4EujZyrMnyjYkhzT1GPmpCWLcwZ9A0WRwzDMExRqMic+s3QRK/FE0V2kWNUUkYOLExN0NjdDrqCGY3HTY5HcdITkAMVTYTycx8UuzPag0RD6Fa5ek/OdI51H/kQVUpdBS2UqUfO3ImtYGZSQ0RbqAZJY5BIavkEMOMEMGqhtJTOuA/s+0Km25EdfpoUNYKI88CK8UBOOtC4f4l9nUpi64UIYWrXtl4t1K75oNeTMeDv6SBqC8kq+t+LMppTfoG0Beg0E5i0Dmjct9wPVXobDQr0EL8xTPmg1+qFHrL2iGy9q+QcqQX4nWYYhmEekJ4AHPlFbvf8H2BqVmJKXRMPO5jr2GThIce64tEjauSZUo56BUYznFv1ICI57BfAq90jHxIenybELkWCevm5Vfgp29RzwjuDZAPVz7aG4ExZVtDqgL4vzccBLx4DxvwBuPoDmYnA/q+lSCLThfCTwLJR8n7vzsDYJVJclYMHLnXGmeKl6nl0poJGG3auQP/Py5VKp0AT+h0XI8X2sBbyeZnyM6p1HRG5jUrKxJrTd6BP6Nb/bAzDMIx2OfyznLS5NQWajnpot2LG0NRTd1LqHnKsiypW61G/m7TqzckATvyqncEZOyQIqJGqIlZbjC/Xw5SoEUVKatpYVOqpn+5SX6z8U1+gmcvPVE//FRNToNlo4IUjwLg/AfdmQFYycPB7YFEfIDVG1ls9QWmF5bPDJ6EYFH4fZBA5MFBaWxsbw1vWFpmHlFpIr4cm2Rcag+TMHGEfT58/pmJQCuxz3RuKbTJm0Ehaq4ZgccQwDMNIUqKB4wvkdq93S0zz0UWnuocc6wqn1RE0m1KiRyd+K1+hPKM+7ocDK58AcjMB38FArw/K/VBFHPUth0tdWfbCX49ujoYutriXmIFZq4KE21u1QN8hMgV5/qBMI/RsIe+nlNVJ6wGr8i8ybD4vo0adGjnDzd4KxoinozU6NXQukvKmKZQoHdXP6ErLAn1jQntvvNnfFyuf61imBb+uweKIYRiGkRz8AchOk1EW30ElHqKLTnXFI0c3Y1ORkV0sx50m5c6NgYxE4PQS7QzQGKHePysnSLtrip6M+q1ctTUE2TYfvy7rdHpXsN6oOPZW5pg3qTWszE1w4EoMftkThmqF/ma/wcBz+4Fn9wLP7ZOpXhVg87kIo3OpKyu1bt2ZOxqLRpC7oSLMjTWFUV0NfMm5rrJRX23B4ohhdJHEO1wbwVT/Z+7UIrlNdsIlrPLFpmSK/HHaRcXRuoarvSVq2ZiDggJXo1Menpx2LWg4enQukJOplTEanTMd2VRHXgBsXIAJfwOW5Tfx2H8lBjl5+fBxs0MDNfTzocjiFyMDxfZPu8PE+asd+vLUaQ1YVez7czU6GZcikoS5xIBmxplSp0B/v6WZiXAhvHhXM1FgEkYZ2XnCBTOwju6lEDOahcURw+gCtPpF7kXkaDSvMzC7KfC9L/DPFJmrzzCa5sC3siFnva5Aw54lHqKk1DVwtoWtZVGjBl2A0jYUUwaaSD5E4DjAvjaQEgmcW1n9AzQ2yKnt0uYH9sk1vSv0cMXCu6IudWUxqnVdkepDP7mzVp7F3fvp0AeUqFH3Jq56twqvbhyszFXNgNeXt+dRBSlsfKFP6WCMemBxVB1QBCDumrZHwegaebnAzUPA9neAn5oDv3aTjkbRwUANE2k9HLxeFu8u7A1cXAvklrO3A8NUhPjrwNllZUaNCqfU6WK9UfG6o9DidUeEmQXQeeaDprD0HWQ0A/WVIsFNDP0J8O5YoYdn5+Zhb2i02O4bUHGXurL4cGgAmtVxED1YZiw/g6ycPOgylDqm1BsNbWFcvY1KY1RBah3VHVGjVnVyPy1LFVUcxil1RgmLI02TGgf8ORxYPAiICdX2aBhtk50BhG4DNs4AvmsMLBkMHJsH3L8NmFkDfkOAEQuAN68B0w8DLSfJVde7p4A1TwM/tQAO/SjtlhlGXez7SjZI9OkD1OtU6mG62Py1dMe6EsQR0fopwLoWEH9NRjUY9XPntPyNIzq/LPv/VJCTN+KRnJEDZ1sLtPRSr1OYlbkp5k9sA0drc+H+9sW/l6DLhEQk4XpMqkglU2cUTZ+hCBql0FKq76GrsWo9947gSOFsSL8ljd3l7wljXFRJHH311Vci3DhrVkEeN4CMjAzMmDEDzs7OsLOzw+jRoxEVJUPjCrdv38bgwYNhY2MDNzc3vPnmm8jJySlyzL59+9C6dWtYWlrCx8cHS5boaQFtfsGKBqVx0EQ4KkTbI2KqG+qOfn617IT+TUPg78flKj012bSqCbSYAIxfDrx1XaaetJwA2DgBHs2AEXOBV4OBHu8Atq5A0l1g14fADwHA1teB2Kva/usYfSf6kvx8KlGjMnggjnQ3cqTqdVRS5Iigmpf2z8vtQ7NlSiujPpLuSWc6sk1vMgDo81GlTvNfQUod9TaiHkfqxsvJBrPHS+e4JUduatz5TB0pdfRakLEEA9FjTTFK2KDm1Drls8BGDMZLpcXRyZMn8euvv6J58+ZF7n/11VexefNm/PPPP9i/fz/u3buHUaMe9MrIzc0VwigrKwtHjhzB0qVLhfD54IMH1p43btwQx/Ts2RNBQUFCfE2bNg07duyA3kFuNE9tlv0MqK8BCSSqLWEMm6QI4OTvwJ8jgG8bAeueBUI2AtmpgEMdoP1zwJObgDevAiMXAP5DSu91Qd29e/yfFEnD50nHJ3IUo/PPaQMsHwdc38eTPKZy7P2cVnEA/6FA7VZlujfdiEvVeXHUpGClNyY5s/R+NvT9M7cBIoLkd4dRD1lpwN8T5GIgNT8dtVD2+6lEGpniFKbUlmiCXn7umNGzkdj+v7XnhemBrkGvxRZVSh1P1ktyrdsRHCV+n9RBdHIGjl6LE9vG7gpozFRKHKWkpGDixIlYuHAhatV6EO5OTEzEokWL8MMPP6BXr15o06YNFi9eLETQsWPHxDH//fcfQkJCsGzZMrRs2RIDBw7Ep59+irlz5wrBRCxYsAANGjTA999/D39/f8ycORNjxozB7NmzSx1TZmYmkpKSilx0BltnORGmiUd6PLB0KHDvrLZHxaib2DC5Ek31QT/4ycjO9b0yXcnVD+j2hrRwJZEz6Fug4WPl7oouMLMEWk0Eph+SgrvJQCpBB8J2yNTN+V2AM3/J1D2m/JCojAqWZhi/9QBWjDeeBQz6HRKpZTWAnu+WeSgZHNBLRR3Pne0soauQUYS3k1xouByZVPpvMqXXEYd+qMbRGTD04djwghSc1k6yuWkFHdkUKCXyTkK6SCPr1tgFmuTVPk1E35y0rFxMX3ZGbZNsdUFpf/Ra2FqYoqevemuv9J1WXjWFm1x6di7+C4lUyzn/PR8h3C5betWEt3P5mvMyhkelxBGlzVFkp0+fPkXuP336NLKzs4vc7+fnB29vbxw9elTcpuvAwEC4uz9YDerfv78QM8HBwapjip+bjlHOURJffvklHB0dVRcvLy/oFJQm9eRGoG47IOM+sHQ4cOeUtkfFVHUycPc0sPsTYE57YE5bYNdHsj6IoPe6z8fAzNPAjONA7/elhWtVnW/o8Q26y8nHS6cLVsFtpZHDppnS6Y4m+slF01mZYu8dCYNdHwO/tAHmd5ZmGHTfle3Ar91lzUSyev7D1Vn2fCavm48D3PzLPFRxqtPlqNFDqXURZUQCOs0ATMyAGwdkjQxTNej7E7IBMDEHxi8DatWv9KkUl7quPi6wsdCsK6KZqQl+ntAKbvaWwv79f+svaKx3TlVS6iiCRj1jmAdQWceDnkfqSa3bfL6glxRH6YyaCoujlStX4syZM0KMFCcyMhIWFhaoWbNmkftJCNE+5ZjCwkjZr+wr6xgSUOnpJdtuvvPOOyJypVzCw8Ohc1An7MnrAe9OQGaiTLm6VbrgY3QQcoujNJytb0gRsrAXcPB7IDZUTrQa9QIG/wC8HgpM2yX7qrj4aG48zo1kFOq1EKDvp4CjF5AWKycqPzYD1r9gPFGQ8vRcIVv0/96T7oAUJaKoARXmm1rKJqHD5wLNRss0M6oL+7k1sP9bIFs/7H4rBP32XN0lP7eUtvkIdLn5a6mmDKXVHRE1vaS1N3G49KwEphyQq+a+gjnBkB+A+l2qdLqdl6I1nlJXvD/W3ImtRW3TxqB7WHbsFnSB3LxCKXWc4lUiI1pKcXT4aiyik6qWNXEnIQ2nbyWI9cchzdkV0Jip0JIMCY5XXnkFO3fuhJWVFXQJMm6gi85jaQ9MWitTd24eBJaNBp5YBTTopu2RMWV1eL+2B7i0RUYVKPKnQBGbxn2lyxxdWxddGKg26Hm7vAx0fBG4vBk4Og+4cwI4t0Je6neT+5r0r1QNgN5CVs3hx2W9F6WPkaGFAtWc0HsWMBxo3E9+N4lWk4AO06XFOkUB934GnF4C9PkQaDZGNhPVd2hlXIka0d/r1PCRD1EiRwE67FRX3M77cmmOdQpdXpHfD/pux1wBXJtUzwANCYq20iIM0XEG0PrJKp2OJrjnwuVvbG+/6ksja1ffCe8M9MNnWy/hky0hCKxbU6RWaZOTN+MRnZwJByszdGui2fRCfaW+iy1ae9fEmdv3hZHCtG6P/i0rjS0FUaMODZzg7qBbc1xGh8URpc1FR0cLF7nCBgsHDhzAnDlzhGEC1Q3dv3+/SPSI3Oo8PGRHZ7o+ceJEkfMqbnaFjynucEe3HRwcYG1tDb3HwhZ4YrV09KGalOVjZefwRiU3XmS0QFq8tNy+vFUKo5xCkQPq9O47UBawN3gMMNehH1FTM6DpSHmhtE2yCQ/eIIU4XWo1ADq+IK11FTFgaOTmALcOPxBEqXIVWmBhLwUiCSKyrS7NBMOrvYz8UW8pSpVMDJemGscXAP2/qHDPFp2DfnduHZI28d3ffOTh1AfmSoHQ0Ke0urCoZOTl5cOkNLczNz+5sHF5C3DkJxk5ZMoPpZ3+Tc506fL71PeTKp9y92X5fW3hVRNu1TxBfaZrA5y6mYDtwZGi/9GWl7qilq32Gq4qjUgHNPOApZkRLWpVkJGt6ghxRA1hqyKONgXJ13tYCxmNYoyXCi2B9u7dGxcuXBAOcsqlbdu2wpxB2TY3N8fu3btVjwkNDRXW3Z06yd4ZdE3nIJGlQJEoEj4BAQGqYwqfQzlGOYdBQJOyCSvlijX9x0KRpLBd2h6VcXM/HDi2AFgyBPjWB9j4IhC6Vb4/1NmdVkWnbgPeuAIMnyMn2bokjIpTty0w5g9g1gWgyyxpG55wA9j2FvBDU2DHu0CCbqSPVJmcLPn92fQS8H0T4M9hwKlFUhhROmuLJ+T3jdwBxywCAoaVLowUKLcicAww8yTQ+wPAwk7WmP3RH/hnCpBwE3obNdr9qdxu+wzgWPeRDwmLThZ9P6gvTN1aur9ARUXaFmYmosg+PCGt7IPpu0GcWwUkqtcS2KChVFNypku+B7j4yt8aWpypIkq9UV9/N63UsHwztrn4/Ny9n45XVwcJca0NqAnutouy1IDrX8pmcPPaMDOpIaLbyiJORaF6M+onRecZ2Ewu1DPGS4V+yezt7dGsWbMi99na2oqeRsr9zzzzDF577TU4OTkJwfPSSy8JUdOxo1xp7devnxBBkydPxjfffCPqi9577z1h8qCkxU2fPl1Eot566y08/fTT2LNnD1avXo2tW7fCoKCJNRWu0kQr9F9g5QRg3J8yKsFUzyQx5rJMqaFUtIhzRfe7BwJ+g6XNNtlnV9VIQVs41gH6fgw89hZw7m/g2Hwg7ipwdI6MLFEEjIQfRUv06W8kVz6KgIRskiI2Q9bECMgti943/+HSvMKsCqu/5tZAt9dlQ15KsSNHQKqxuPyvjMLRvkq6cmkF+q25d0amFXZ7rVwPUaXUeTqICaSuQ0X2jd3sxLgvRSSjnrNt6Qd7tZNppxRZpe9Df7I2Zx7527lxpvwcUUNd4UxX9XTLtKwcVUPP6qo3Ko6DlTnmT2qDkfMOY19oDObsvYqXezeu9nEcuRYnrOipCS656TGl42RrgR6+rth1KVr0PHprgF+lo3TkjqjNaCGjG6g9eZ7stocMGSKav3bv3l2kyK1bt06139TUFFu2bBHXJJomTZqEJ598Ep988iAcTzbeJIQoWtSiRQth6f37778LxzqDg+yZxy4F/IcBuVnAqklyssdosCj/BPDf+8AvrYF5HeWEVwijGoB3Z5k29XIQ8MIhoOc7skeVHkwIy5XO2W4aMOMk8MQ/QMMeskkxpZ/90U+aS1xYI00ndLmPCn0/1jwjo3vUUJdqRkgY2brJSAjZ5r8RBgz7BWjcp2rCqDD27vKc0w/KdMrcTODwj8DPrYBTf8h0Pn34/O8pmPxTXRX10CoH+tD8tbTUujJNGRTIOIU4tVim1DJlc/A74OIaaeZBC3rlqFkrD4fCYpGZkyeik74F/aq0gb+nAz4bESi2Z++6goNhMdU+BmWyPijQU4h9pmxGtpIRcDLUqGi0j9wJN3MvKaYQNfJ1ybNSjZCzHVl6k3MdRbB0HppYrX9e/odTwxQYvbDANYtRS8oV2fVSXQGtmqcUqmejmouGPWWUgfoGUdNeYyIqRK6Wn18tJ/uEfW2g/bNAmynSgl7bZCYDV3YAlzYBYTtlA1wFGiulyFENkVeH6jOboJ9NGhM538WFyfvcAoB+nwE+vaGzkPhd+wxg6QjMOidX/cvB2AVHcPJmAmaPb6GahOg6Cw9cx+f/XsKgQA/Mm9jm0e/nr92AyAtAj/8BPd6urmHqH7Q4sXqy3B4yG2j7tNpO/daac1h96g6mdK6Pj4Y1hbahxrArT4aLyATVH9WuWT0ppZk5uWj76S4kZ+Zg9fOd0L6BDvwO6zgZ2blo95l8zVY+1xEdKxBtu3g3EUN+OST6ap16rw/srSrQf5AxSG2g2QYCTPmhXO1Rv8mVuPMrgbXTpGBqMV7bI9Nfru4GglYAYf8BmYWaQVo6yFovEkRURGyoxgTlwT1A1k/1+UhGP04slDUEuz8G9n8DtJwAdHih+l280u9LZ0CaiJHdtCLcCKr/IjFEKXN12mjHPY4iib4DpBCi141sjKNDgGWj5GeLRJKrL3QK+j2h/ldE55fKLYxoFfZB5Ej3neoe6nVUnsgRvZ9dXwXWPC1NNzrPlJFWpigUYadFPKL982oVRmRbvbvAwruvllLqikMC7cLdRJGeOXPFGax8rpOoZdM0+0NjxCSfGi63rVe+76mxY2VuioGBHkJcU2pdRcSREjXq5efGwogRsDjSJWjVe8Q8wNQcOPuX/E8oL1ta7TLlJzMF2P5/8jVUsHMHfAdJQVS/ijUohoiti6xJImvji+uAY3PlKjpN/Oni0xfo9KKMsmkqxZDSmcgdkNL8qJcUffYVnBpJQURRIs+WupPmSN/VDs8DgWOBA98BJ36VYpyEOU0ce7wD2OpIvQDVm1FPJxtnoOP0cj/sVnwaUrNyxapqQxf9EQxKr6ObsaliVZkmT2VCYpvcHMm0hOrKKvAaGQXUVJqc6ShyS78DlH6sRoLCExCXmgV7KzOdiZTQZ2b+xDYY8stB4Yb25bZL+HCo5iNaSiNS6rVTqtMi8xDUEJbE0dYLEULYPvI7X7D4s6Wg0e4wTqljCmBxpIsCaejPMt2L3LY2zpA1IG2nantk+gF1ul83DYi/LmuIaILa4nGgTlvD6E9THTVwFC2i14zssKlfEqUiXt0pL67+0oSg+ThpVFBVUqJluiMJohsHgfzcB/tc/QoE0XCZsqYrgqgkKP1wwBdAu2dkPRsZRJxcKNMVH3sTaP+cfG21RU6mbAxMdH2tQtFSpfkriQ19qn2gxp61bMyRkJaNsKgUBNZ1fHT0nnqFbXkVOPKLfC9J/DLS/GTVRCDpDuDsA4xdrBZnusLsDJFRox6+bjDXoc+Zt7MNvh/XEs/+eQqLD99Em3q1MESDDVnJlEJx7OP6l4rRsYEzPB2tEJGYgb2XozEw8NGNXM+GJwhnQjtLM/Ssxr5ajG6jO79AzANoEj/4e5nORGyZBRz/Tduj0v1mn/u/BRb1lcLIoS7w1GbZrZ1c2FgYVQwSIvW7AhNWAC+fkcX7ZGUdcwnY/DIwu6lsIkp9TipK0j35eV48GPjeV05GKVJEwojML3q+B8w4Acw4DvT8H+DeVLeFUWGcG8nXjD579LdkJsq6pLkdZIqgtko8Ty+VvZrsPeWkvwLoU/PXwpCr3oPUukJptWVBlu8UZSYRQPVZjPzM0nf+zknpSDdhVblTMivCrktROpVSVxga0/THGontt9ecF7bPmoJSC9Ozc+HtZIPmjxL0TBEoyja8pexRtO7s3Qr1NuoX4F6uSBNjHPCMUVehyeCAL2VtALHtTeDIHG2PSjehfjOLB0nXOZpgNx0lneYadNP2yAwDcqIa+DXwWgjQ73PA0RtIiwMOfAvMbgasex64F1T2Oe7flp/fRf2AH/zl55makJJbXu3WsubppTPA9EMy0qJr9ToVhezDn9svm4rSZJtStaiIfclg4N7Z6nf4I3cxovsbFY74BeuhU52Cn4dD+R3rlPYKHV+U2+RESO5+xg69DudXSaMgclZ18VH7U9yITRWCg3rMPNZEN01x3ujXBB0bOokU0xeXnxYRHk2wReWa5qkXtvm62BCW2BcajYTUrDKPzcnNEyl4BEfpmMKwONJl6Iex76eyjwrx37vAwR+0PSrdWtGkxo3zuwLhxwALe2Dkr7IZoQZWNo0eWjWmQvWXz0r7Xq+Osi6IDER+e0wKVOoZRVE8Iu4acGg28FsP4MdA+fkNPy73kbMcCa1XzgPP7ZXF8BR1MbQUWaoXJNHX/S3AzEqmKtLrsX66jKBVByd+kw6NZGTR6skKPZTMTEMK0ur0UxwV2HlXpDEkpeKSmx/1QCNTEGOGennt+lhu0wJJo54aeZrdBVGjDg2dRKNhXYRSSn+e0Apu9pa4EpWCd9dfFN8PdZKUkY29odI2nCfrlYOixWTFTk2rFeFTGseuxyM2JUuk33Zt7FJtY2R0H6450geB1Ot9WYNEjljkIkY1SMZuNUtuZltfAy6ulbdpoj7qV6BWfW2PzPChWgOlFujuadlUlpqi0sSfLvQekFCNulDoQTWAel0KXOaGAA5G9B+/pR3Q612gzVPA7k/kKjyZI1CdVeeXZZ2LppzRqP8TrfwTZA5RQSOS6ORMMXmgmnAlCqNPVMixToEa+lLq4aEf5IWachvjCn7kRemainzZP4zs/TXEzoIamz7+updSVxg3eyv8MqEVnvj9ONafvSvqjyZ1rKe28+8MjkJWTh583Oy02udJ3xnVqg4+j0gSrnVlvT9KLymqTdKlOjdG+/CnQR+g/5h7/B/Q+wN5e98Xst7DMFtUPZqbh4D5XaQwolQPqlGZspWFkTYgK+3RvwOzLshCf4rYUZojCSN6b6jRLPVCeeMKMHUr0OE54xJGhXGsK+36p+2RYp5cv/Z/BfzSRlrOayKFiww10hMAlyZA84q3BVAsvBu52sHaQv/y8ZsUTDBjkjMRl1LIDv5RkOmIqaWssyHBb2ykxMgGy9mpsuExRY00BKU+nbqVoBfiiOjQ0Blv9Zdpv59sDsH5O/fVdm5VI9LmtTmlrgoMa0mvH8Tn6nZcob54xXpJbbtYkFKnQYMNRj9hcaRPUHod9U8hqN5j5wfGJZComeuuj4AlQ2TBNNnuPvOfrFFRs3MSU0FI8PT5EHg1RKY2jpgPvHkVeHKjTFOyYxcgFXXbAE9vB8YukaluyRHAhheAhT2Bm4fVa41+dK7cJmOLSjTIDdbjlDrC1tJMFLZXqO6IoM+r0kKBUkONCXI2XDVJGnhQvSF9TjXo2rfvSrTocUQpkF4F75Wu81z3hqKAPys3Dy8sO/PI2pbyEJ+ahUNhsWJ7SItHu6wxpePuYIUujWSa3Iagko0ZDl6JRVJGDtwdLHXGOp7RHVgc6Rtk0DDwG7l95Gdg+zvGIZBiw4BFfQomKvlAq8myeL9uW22PjCmMhY20AW/5hLS3ZkqGljWbjgRmnAT6fCzTECOCgCWD5MRUWNFXEUqny0qWrnnUw6cSPDBj0F/XrEql1im/tTVMZBPiiPMwCuj/EnKPpBpOywJnOg1/j3cVWHjrQ9RIgaI6345tgXrONsIG+rXVQaJfTlXYfjESOXn5YiGCIrWMeowZKLWupNqwTQUpdYMDa8OUe0kxxWBxpI9Q08nBBcYMx+cDW183XFcl+lE7uQhY0E12Z6e0rXF/AcPnyFoOhtFnyB2t6yxpckERNpqMX9oMzGkP7HhX1tZVBrJYV+z/qWaxklb2+uxUp+CvmDJUVBw5NQCajZbbSt2WoUP9nYKWy88h9TJybaLRp6PUpv1XpAFBHx208C4LMo6YN7G1aI5MJgrz9l2t0vmU+hc2YlAP/Zt5wMrcBNdjU3HujoyAK5DToFLnRil4DFMcFkf6ChUMDyNrb0qsXQRsecXwBFJqLPD3BGm8kJMu61deOAIEDNP2yBhGvdi5ytos+nw36i1dAI/OAX5uBZxYCORW0Db44PfyO1O3HdC4X6Wds27Hy3z9AD0WR74FRhKXK+JYp9BllrwmwxF1RPN0mSs7ZKo20f9LwKe3xp/y+PV4pGTmiIa9zevoX3SSIqqfDm8mtn/YeQWHr8q0uIoSnZSBYzfixPbgcjQuZR4NNXXtF+Chih6V1kuqBfeSYkqAxZE+03qyrO+gVb4zfwIbZzywUdZ3wnYC8zoBV7ZJp77+XwCT1htvMT9jHLj5A5PXARPXAC6+QHo88O8bwPzOwJX/ypdCSz2lTi1+EDWqZGG3YsZQp6Y1atpUzOVOF9PqrkQmVzz1yaOZFJfUj4uiKoZK9CVgDTUHzgdaPyWzE6oBpfFrH3830cBTHxnXzgvj2tYFfbRe/vssIhMzKnwOspymr3Zr75p6U3elT6l1FJXLzs0rIUrHvaSYkmFxpO+0GA+MWiidwc6tANY/X/FVZl0iOx349y1g+RggNRpw9Qee3QN0mlHp1CCG0Tsa95VRpEHfATbOQGwosGIssGwUEBVS9mP3fy0jT9SItuFjlR6CIaTUEfWdbWBhZiJWipVIWIWgHlzE2eVAspzMGxSpccCK8bI+rV5X+Zmrhgkj1YHs0hML70fxyfBmCPB0QFxqFmasOFNkIl4eOKVOM3Rr7AJnWwvxvihmF4np2djHvaSYR8CzTUMgcIzMDzcxAy78A6x9WvZC0jciLwC/9QRO/Cpvd5guG4RSQTnDGBvkwEi9ZaiJLJkDmJgD1/YAC7oAm2dJu+XixF4Fgv6W270KUqQqyQOnOv1OO6HmnY3d7CpnykB4d5JNi3MzgWPzYHAOoKsnA/dvyVYI4/+qcC+sqojve4kZsDY3RRcf/W7AaWVuivmTWsPeygynbyXgq22Xy/3Y8Pg0nLl9X+hRTqlT/3dfEUDrClLr/guOFC6DTdzt9LJ3G1M9sDgyFKi5JhkV0ASKmkuufkpasuoDVCt1ZA6wsBcQcwmwcwcmrZW9NcyttT06htEu1jWlhf/ME4D/MJnidXqxrEci98bsQmk81AMtPxdoMgDwalelpw0xkMgRoUyCKmzKQNCsVYkenfpDNtY1BBLvAJtfln2cyC2xGpzpSkqpo9V9Ehf6Tj1nW3w/toXYXnToBv69IHvolCeljujYwBluDlYaHaMxp9aRKErOyFa51HFvI6YsWBwZEn6DgAl/y+aFoVuBVZOLTpx0kaR7wLKRwH/vArlZgO8gmU7k00fbI2MY3YJ6ztDK/tRtgGdLmQZFfb/mtgMurgMiL8rGyETPd6v0VBnZuQiLThHbTesYgjgqcKyLkoKvwjTuL1N8M5Oke6Y+knBLNhveMAP4qQUwuylw7m9ZszrmD8DNr1qHo6o30jOXurLo19QDz3dvKLbfWnMe12Pkd6gsOKVOszSv64iGLrbIzMnDiuO3ceSaNL7g15spCxZHhlir8MQqwMwaCNsBrJwg63h0EYpwUaH59X2AuQ0w5Efg8RWArX6nWDCMRqnXGXh2rzRjsa8tDRjWTAX+6C/3U/8kz+ZVeoorUcmiMaeTrQU8DGA1u9K9jhSo3pEs14lj83X3N1WBqvvJXe/MX8D66cDsQOCn5rLZcNAyIOGmFEW1W8ma1SaVczSsLBGJ6bh4N0kE5Xr5GVaD6Df7+4qmouTCRw1iyTa6NEg8UXqhmUkNDGgmndUY9UKGC0r06PudV8TvGgmm+i622h4ao8OwODJEGvUEJv4DmNvKGoXlY4GsVOgMmSnSWW/1k0B6glwFf/4A0HZqtRQCM4zeQ5N1arb70imgx//k4kJWipzw0u0qUtiMwRDcnJTI0c3YVBEVqxTU88jRWxrFUARG18QQ1ZudXgKsfRb4IUCmXW6aKaNDibelaQ9Zu5M9Obkhvn0LeG6frFmtZnZdko1fW3vXgoudJQytzmXOhFbi7wqNSsZ76y+W2ISU2HJeptR1bewiFiIYzTC8pRRHWTnSKGMYR42YR2D2qAMYPaVBN1m3Q65vNw8Cy8YAE1cDlnKSoDXunALWTgMSbsgeTZTL3+OdaisCZhiDwsIW6PG2tPWniAZZgauhcadixqDP/Y0KQ310atmYIyEtG2FRKQisTG8TU3NpjLHtTeDIz9LymkwztCaGrgA3D8nLrSNASmTRY6j+tE4boH4XoF4XaSqhI42zDcWlrjSodmjOE63wxMJjwgigbX0nPNHBu8gxJJiU+pchXP+iUbydbdC2Xi2cupUgjS+as/EFUzYsjgyZep2AyRuAZaOB20eAv0YBk9YAVlpwnyJ78UM/APu+kgXjjl4yLYj+42YYpmpQ/69+n6rtdA8iR/rtVKdA0S9KrTt2PR6XI5MqJ46IVpOA/V/JtLSQDdUXdSHTmpjL0jyBFrtIDKUWcyukfnAUGSIhRL+rddsDFrrXM4fSzY4W1H30DTCslLrCdGzojDf7++Hr7Zfx0aZgBNZxLPK5o6jS1egUWJiaoF9TwxSJusSYNnWFOCLjC09HNnpiyobFkaFDjlVPbgD+GgncOQH8OUI2mbSuVX1joInEuueA8OPyduBY2UuDXLgYhtEpKCf/ckSywTjVFXasI3FUKcc6BRIbHV4A9n4GHPpRptppIu2QxFB0cNHIEDUELoyZlRRD9btKQVS3rV64ex68EiOslKn/VCNX3YhkaYrpjzUU1t5kPvHC8tPY8lJXVUNlxYihh68rHKzMtTxSw2dcWy/YWJqhff3qc2Rk9BcWR8ZAndbAU5uBP4cD984AS4cBT27UvG0rpX6cWwn8+6Z01rJ0AAZ/DzQfp9nnZRim0tyITRENU6n/TH1nwylafuBYVwVxRLSfBhz+EYi6AFzdJU1wqkpeLhB5Hrh5WEaHSAxl3C96DNWVebWXjVpJENHvupn+1evsVFzq/N0Nop6tLOjv+35cCwz95ZBoQPz66nNY+GRboac3n5P1RuyaVj2YmNTgWiOm3LA4MhbIvWrKVuDPYfI/4SVDpECyc9XM85HRwpbXgOB1DxopUhpdrXqaeT6GYdSaUufvaQ9TE8OZvFbZsU6Bou5tpgBH58g+U5URR5RmHHEOuEWRocPA7WNAZrH+SRZ2sk6IhBBdyLhGz2szc3LzsPdytMFZeJeFo7U55k1sjVHzj2D35WjM338NXX1chFiiBYje/oabWsgw+gqLI2PCPUAKpKVDZcrGksHAU5sAezVbiN44KO1jk+4AJmbScIGMF0z0v9Efwxg6hlZvpNDEXYqjmORMxKVkwrkqLmmdZgDHf5VRntvHAe8OZR+fmw3cO1uQIlfwGIqmF4Yi694dC9LkSAy10J7hg4agFDMyxSDBQAXyxkKzOo74ZFhT/N+6C/j+v1DsvxKjEog2Fob1HjOMIcDfSmPD1ReY8q8USLGhBQJpsyzorio5WcDez4HDP1FOHeDUCBi9UDomMQyjFyhOdYZUb0TYWprB28lGrNhT3VFnnyqII/q9bDkBOPOnTLHz/rvo/pxM4O6ZB5Gh8BNAdrF2CmSMQ7VCioGCR3ODX0BSGr9SbyOyvDYmxrfzEoYAa07fwYkbsn5sKLumMYxOwuLIGHHxAaYWCKS4q8DiQVIg1fSq/DljrgDrpslUEYJsbvt/oTPWsQzDPBqyFw4x0MiRUndE4ohS6zr7VLHZdOdXZJPV0H9lVIh6yYmaoUNSDOVkFD3e2kk28FUMFNybGrwYKv7Z2llg4d3XSFLqitcffTq8GS7eTRSfP3srMzzmq6G0doZhqgSLI2PFqYEUSFR7RD2HlhQIpFr1K266cOoPYMe7QE66nAAM+xnwH6qpkTMMoyEiEjNE2pOZSQ008bAzSHH0X0hU1RzrCi8yBQwDQjYCv/V4eL+NS0GPIaoZ6gK4+svmvUbKtZhU3IxLE9bV3ZsYpyiwtjDFgklt8NrqIAxuXhuWZsYjjhlGn2BxZMzU9AambpMRpPhrwOKCGiTnRuV7fEoMsOkl4Mo2ebtRL2D4PMCBUwUYRp/rjXzc7Axy4ubrIVMFL1fVsU6h62vA5a1AXg5g5/4gRY4EEaUwG7gbW2VS6jo2coadpfFOPeq72GLdi9zfj2F0GeP9hWIkjnUepNhRx3Ulxc61SdmPC9sJbHhBNiI0tQT6fAR0mG7UK6MMYzj1RoaXUlfYse5KZDLy8vKFvW+VqN0SeLGgfxstKrEYKpVdSkodu7MxDKPj8EyWkW515GLnFgCkREqThuhLJR+bnS77Fi0fI4URPea5vUCnF1kYMYzBONUZlhmDAjUetTAzEX2cqPZILVB6HV1YGJUKuQOevp0gtnv7G1+9EcMw+gXPZhmJnRvw1BbAIxBIjZYCKfJC0WMizsvc+hO/ydsdXwSe3SsLixmG0XtCDFwckUNaE3c79fQ7YsrNnsvRojyVPle1a1prezgMwzBlwuKIeYCtM/DkJtlsMC1OptrdCwLy8oDDPwO/9wZiLsvc+knrgAFfAuZW2h41wzBqICE1C3fvp4vtAAMVR4Svu/zb1GLKwFSo3qgPR40YhtEDuOaIKYqNE/DkRpk2d+ck8OcwwL2ZbFxI+A0Bhv4shRTDMAZDSISMGtVztoG9lTkMFXKsI0Kj5N/LaJaM7FwcuBJrtBbeDMPoHxw5Yh7GuqaMDHl3AjISpTAyt5GiaPwyFkYMY4AYavPX0kwZOK2uejh6LU7UeHk4WBn8Z4thGMOAI0dMyVg5ABPXAJtmAhlJwMBvZNExwzAGbsZgmE51xSNHN2NTRVTDytzwLMt1iZ1KSl2Am2iEyjAMo+uwOGJKx9IOGLtE26NgGKYaxZEh1xsRrvaWqGVjLprdhkWlILCuYYtBbUJ26YqFN9cbMQyjL3BaHcPoGPn5+dh87h7+C47U9lAYIyE9KxfXY1LEtqGnPlH0wk9pBhvJdUea5MLdREQnZ8LWwhSdGnE6NsMw+gGLI4bRISjN59VVQXjp77N47q/TWHH8traHxBgBlyKTkJcvoypu9obvQKnUHbFjXfW41D3m6wpLM05fZBhGP2BxpGES07Lx9fbLGPfrURERYJjSIBvlMQuOYEPQPdV97224gG0XIrQ6LsbwMfTmr6U71rE40iQ7OaWOYRg9hMWRhjE1rYE/j9zEiRvxOHY9XtvDYXQU+nwMn3MIF+8mwcnWAiue7YDH23mJ1fxXVgbhyDVphcswmiDESJzqikeOLkWwONIU4fFpwhHQpAbQ09dN28NhGIYpNyyONIydpRmGt6ojtpcfv6Xt4TA6yLJjt/DEwmOITcmCv6cDNs7ogs6NXPDZiGbo39QdWbl5eO7P07h4V05gGUbdGItTnUITdymOYlMyEZeSqe3hGCS7C1Lq2tZ3Qi1bC20Ph2EYptywOKoGnmjvLa53BEeK/4wZhsjKycM76y7gvQ0XkZOXjyHNPbH2hU7wcrIR+81MTfDT463QoYETUjJz8NQfJ3AjNlXbw2YMjOzcPFXPnwBP44gc2VqaiWa3BNcdaYZdl6LFdV9OqWMYRs9gcVQNNKvjiJZeNZGdm49/Tt3R9nAYHSAmOVNEi/4+cRvU+uOtAb74ZUIr2FgUddenHiwLn2orJq1xqVmYvOg4opIytDZuxvC4FpMihDpFub0LhLkx4FsQPeJmsOonKSMbx67Hie0+ASyOGIbRL1gcVRMTO8jo0YoTt0TvB8Z4OX/nPobNOYRTtxJgb2WGP55qhxd7+JTaINHByhxLn24vVrrvJKSLCFJiena1j5sxTILvFvQ38nSACRWIGAkqUwYWR2pnf2iMiIY3crVFAxdbbQ+HYRimQrA4qiaGNK8tJsLh8ek4eJWL642V9WfvYOyCo4hIzBAThw0zuqCn36OLlcli+a+nO4hrWumetvSksP1mmKoSEmEczV+L48u9jjRu4c1RI4Zh9BEWR9WEtYUpRreuK7ZXsDGD0ZGTm4fPtoTg1VXnkJmTh95+blg/owsaudqV+xzezjZYOrU97C3NcPJmAmauOCPOyzBVIdjInOqKO9ZdiUrhaL6aa9j2XuZ6I4Zh9BcWR1pIraNC1chErhsxFu6nZWHqkpP4/dANcXtmTx8sfLKtSJerKLS6//tTbWFhZiI+R2TowP2zmMpCn50QI3OqU6jvbCO+R+nZubgdn6bt4RgMJ2/GIykjR7QkaOVdS9vDYRiGqTAsjqqRxu72aN/ACbl5+Vh1Mlzbw2GqAapnGDbnMA6GxcLa3BRzn2iNN/r7Vqm2o0NDZ8yZ0Er0D/nn9B18vT1UrWNmjAeqYaOJrIWpCRq7lz+KaQiQG2STgr+ZTRnU3/i1l58bTI2oho1hGMOBxZGWokcrT97mlCgDZ/vFSIycd1isStetZY21L3TG4Oaeajl3v6Ye+GpUc7G9YP81LDxwXS3nZYwzpa6Jhx3MTY3vvwNfd5lKyKYM6otEKvVGfbneiGEYPcX4/jfUMgOaeYh0AyrI3xcao+3hMBqA6hd+2HkF05edRlpWLjo3csammV3VXvA+rp0X3h7gJ7Y///cS1p5mm3imks1fPY0rpe4hx7ooNmVQB1S/RaZDlK7YrbGLtofDMAxTKVgcVTOWZqYY20YaMyxnYwaDg5q1Pr/sNH7eHSZuT+1SH38+3V4IYk0w/bGGmNa1gdh+a+157LksV20ZpkLiqI5xmTEUN2W4HMGRI3WgRI26+rg81LONYRhGX2BxpAUmtJepdfuuxCCcC4ENhpuxqRg597DIuaeV02/HNMeHQ5uK2gZNQb2R/jfIH6Na1RG1bC8uP4NTN+M19nyMYWGsTnXFI0c341LZGl+N9UZ92KWOYRg9pkKztvnz56N58+ZwcHAQl06dOmHbtm2q/RkZGZgxYwacnZ1hZ2eH0aNHIyqq6Er27du3MXjwYNjY2MDNzQ1vvvkmcnJyihyzb98+tG7dGpaWlvDx8cGSJUtgSNR3sRUra2QyRrVHjP6z/0qMaOwaFp0CdwdLrH6+E8a29aqW5yZzh6/HNEdPX1dkZOfh6SUnuYaikhbEfx27pZrgGTqxKZmISsoE9R72K+j5Y2xQ3zCK6pKTd1hUiraHo9dEJ2cgKPy+2O7t/+jebQzDMAYhjurWrYuvvvoKp0+fxqlTp9CrVy8MHz4cwcHBYv+rr76KzZs3459//sH+/ftx7949jBo1SvX43NxcIYyysrJw5MgRLF26VAifDz74QHXMjRs3xDE9e/ZEUFAQZs2ahWnTpmHHjh0wRGOGVSfviEkZo78FyL/uv4api08I169W3jWxeWZXtPSqWa3joGL6eRPboE29WmIcT/5xnKOSFSAiMR0TfjuG9zdcxHN/nRJ2xMaSUtfAxRa2lsaZAkWRV1/3gtQ6bgZbJfZckr2NWtR1hLuDlbaHwzAMUz3iaOjQoRg0aBAaN26MJk2a4PPPPxcRomPHjiExMRGLFi3CDz/8IERTmzZtsHjxYiGCaD/x33//ISQkBMuWLUPLli0xcOBAfPrpp5g7d64QTMSCBQvQoEEDfP/99/D398fMmTMxZswYzJ49G4YEdQ6nVUtavTWWlWpDg9JwZq0KwpfbLouV5/FtvbDyuY5w09LEgBoNL3qqrbAnpojAk3+cEJ8vpmz2hUZj8M+HcOpWgrhNEd1XVwUhOSNb20OrppQ64zRjKF53xNFW9dQbcUodwzD6TqWLISgKtHLlSqSmpor0OoomZWdno0+fPqpj/Pz84O3tjaNHj4rbdB0YGAh39wc/nv3790dSUpIq+kTHFD6HcoxyjtLIzMwU5yl80WVopZ8m0wQbM+gfd++nY8yCI9gYdA9mJjXwyfCm+Gp0oDDc0CY1bSzw59MdUKemNW7EpmLq4pPCJIJ5GLLS/3bHZUxZfBLxqVmi7mbLS12F7Tr1//l0SwiMwozBSOuNitcdca+jypOelSt6uSkLfwzDMEYlji5cuCCiRVQPNH36dKxfvx4BAQGIjIyEhYUFatYsmk5EQoj2EXRdWBgp+5V9ZR1DYic9Pb3UcX355ZdwdHRUXby8qqfeoyo83t5L5PsfvhonJrKMfnDiRjyG/XIIF+8miXqFv57pgCc71RcpOrqAh6MV/nxGOuRduJuI5/86hcwcLjYvTFRSBib+fhxz914Ttyd19BZ9qJrVccQP41qK7+XqU3ewI1j+LhkiISyOijrWsTiqNIeuxiIzJ08syihik2EYxmjEka+vr6gFOn78OF544QU89dRTIlVO27zzzjsitU+5hIeHQ9epW8sGPX1l4erfJ9iYQR9YduwWnlh4DHGpWQjwdMCmmV3QqZEzdI1GrnZYPKUdbCxMhfimNDFys2NoMSIWg38+iOM34mFrYYqfJ7TCZyMCYWUuo37tGzjh+e6NxPY76y6IQnNDg6KJyoKMsafVNXG3F2KYUlDjOA21UuwKedD4VVcWiRiGYapNHFF0iBzkqKaIojUtWrTATz/9BA8PD1E3dP++dKtRILc62kfQdXH3OuX2o44hdzxra+tSx0WRLMVFT7nokzHDP6fC2UpWh8nKyRMT5fc2XEROXj6GNPcUkQYSuLpKC6+a+HVyG5ib1sC/FyLxwcaLwkDCWCFxOHvnFUxadByxKVlihXvzS10xrEXth459tW9j+Hs6iHS7/1t7weBet0sRMmrk6WilsR5c+gKZUXg7ye8x1x1Vrun17oL+alxvxDCMIVDlBix5eXmi3ofEkrm5OXbv3q3aFxoaKqy7qSaJoGtKy4uOlq42xM6dO4WQodQ85ZjC51COUc5haPTwdUNtRyskpGVj+0XDTeHRZyhyMGHhMRHdo0XRtwf44ZcJrYQBgq7TrbErZo+XaWLLj9/Gj7tkc1pjIyaZDCqO46fdYcJw4fF2XtgwowsautqVeDzVjv04vqXoV7XncjT+PqH7keiKEHzXuPsbFeeBYx2Lo4pyNvy+WGywtzJDh4ZO2h4OwzBM9YojSl07cOAAbt68KUQO3aaeRBMnThR1Ps888wxee+017N27Vxg0TJ06VYiajh07isf369dPiKDJkyfj3Llzwp77vffeE72RKPJDUB3T9evX8dZbb+Hy5cuYN28eVq9eLWzCDRFTkxp4vKApLBsz6B7n79zHsF8O4/StBPGf/x9PtcMLPRrpVerIkOa18cmwpmKbxMGfR2/CmDh6LQ6Dfj4o0gutzU0xe3wLfDW6uSqNrqxalLf6+4ptMmegJr+GZsZAqaFMYVMG3Tby0WWXOlroI6MhhmEYfadCv2QU8XnyySdF3VHv3r1x8uRJIXD69u0r9pPd9pAhQ0Tz1+7du4sUuXXr1qkeb2pqii1btohrEk2TJk0S5/vkk09Ux5CN99atW0W0iFL2yNL7999/F451hsr4dl5CJJ28mYArUbxyqSusO3MHYxYcRWRSBhq52mLjjC7o6aefzQ0nd6qPV3o3FtsfbgrG5nP3YAzpPr/sDsPE34+JyBFZnG9+qQtGtqpb7nM83aUBOjV0Rnp2Ll5dHSQc7gxKHBl5vZGCb0ETXE6rq3y9UR9u/MowjIFQI9/QkukLIHc7imaROYM+1B9N/+s0tgdHYkrn+vioYJWf0Q40Af5q22X8fuiG6j99Sk2ztzKHPkNf9fc3XsSyY7dFHdIfU9qJtDtDhArrqQeVYi88pk1dYbduY2FWKdv2AT8eQHJGDl7r2wQvF4hMfa6fa/rhdmTn5uPgWz3hVVBvY8xcjU5Bnx/2i8hi8Mf9YWKiP5FhbULR1B7f7RPtDE6/1xeONvr9G8kwjGFTXm3AMXAd4YkCY4a1Z+4gLYv70miL+2lZou+NIoxe6uWD3ya31XthRFAq4MfDmmFwoKeYGD//12mcCy9qoGIInLwZL5q6kjCyMjfBN2Oa47uxLSoljAiyJ/50eDNVWqK+v2Zh0cni/Xe0Nhc9nRigvrMNLM1MRITwdnyatoejdyl15PDIwohhGEOBxZGO0NXHRTgm0er0lnMR2h6OUUIpNcPmHBY9O8gCe97E1ni9n69BrSJT+uYP41ugi48z0rJyMWXxCbFqbihpdPP3XcPjvx0TqZANRSpkV4wraLZcFYa3rI3BzT2F4x2l11HTS0OoN9Kn2jlNYmZqgsbu0pyDTRkqLo7YpY5hGEOCxZGOQBNwJXq0nHseVTvbL0Zg5LzDYtXYy8ka617sjEGBnjBEyInt18ltEVjHUbgkPvXHCUQklt5gWR9ISM3CtD9P4evtl4WAGdGyNjbP7Kpq8FlVSER8PqIZ3B0scT0mFV9tuwR9hZu/loyvO9cdVTTKTnWyBIsjhmEMCRZHOsTYNnVFLQil7VwssNplNB9t+OG/UExfdkZEUjo3csamGV3hV1CgbajYWZphydR2aOhiK2pqSCDRZEcfISdBaupKlttkvf3lqEBRI0b9a9RJTRsLkZ5HLD16C/uvxEAfCb5XYONdx7A/4xWFHesqxr7QGLEQQTbo3s5ct8YwjOHA4kiHcLazxIBmMlpBPWkYzZKckY3n/jqNn/dcVTmT/fl0e9QykqaY9Hlb+nR7EQ25EpWCp5ec1Kt0MTKY+P3gdYz/9SjuJWaIupH1L3bGhPbeGksXIwMLMk0h3vznnIhY6dtiwIPIETvVFUaJMnLkqHzsVFLqAtiljmEYw4LFkY4xsSC1bmPQXTF5ZzTDjdhUjJx3ROTMU7Th+7Et8MHQAFF7YEyQU9mfT3eAg5UZzty+jxeXn0a2HthVJ6ZJYfvZ1kvIycsX9UCbX+paLRN+agJM1u7RyZl4d8MFIdL0hVvxaUjNyhXmAxQ1ZB7g5ynF0c24VGRk688igbYcD/eHysgpp9QxDGNoGNdMUA/o0MBJTLwoxWtjkOH3otEG+0KjMXzOIWFEQFGT1c93wug25e99Y4gr5mTrTc5ue0Nj8Naa8yLCoKtQ2ungXw5iZ0gULExN8OnwppgzoVW1OQpaW5jix/GthH3xvxcisSHoLvQtpc7P08HoFgIehaudJZxsLUAf/bAowzAp0RTHb8QhJTMHrvaWaFG3praHwzAMo1b4f0cdg9KBnuhQT5Vap0+r0roOvZa/7r8m0seSMnLQ2rumKNpv6cX/ubet7yTc+cjNbv3Zu/j830s699mj8Sw+fANjFhzBnYR04e649oXOosFtdbuuBdZ1xKw+st/RBxuCRd2WPjnVsRnDw9BniOpnCK47KhtamFB6wBmSmyfDMAzB4kgHGd26jkh7uRSRhLN63lNFV6BamldWBuHLbZfFyvDj7bzw93Md4eZgpe2h6Qy9/NzxzejmYnvRoRtYsP86dIWkjGy8uPwMPt4cInr09G/qLtLoSKRoi+mPNRICOzkzB6+vDtLpaJsCi6Py1R2xnXfZixS7VOKIU+oYhjE8WBzpIOSKNaR5bbG9/BgbM1QVWtWnaMOmc/dEKhSlYZGjGVlaM0Wh9ML3BvuLbbLFXnVS+58/cm4c+sshbLsYKdwcPxgSgAWT2ogmptqE0tJ+GNdS9MQ6dj1eCEpdn9SGKE51bMZQpmMdmzKUTkhEkjBAoTTcLj4u2h4OwzCM2mFxpKNM7CiNGbacvyeKz5nKcfx6HIb9ckismFM9wbJpHbSShqVPTOvWUERFiHfWXcCO4EitTeb/OnYLo+Ydwa24NNSpaY1/pnfG010b6Mz7V9/FFu8PCRDb3+4I1el0LDKQiE3JEqmTighgisKRo0ezKyRa5dxoZc4LTAzDGB4sjnSUVl41xQQmMycPa8/c0fZw9JK/T9zGxN+PIy41S6QRbZrZBR0bOmt7WHrB2wN8Ma5tXZGC+NLfZ4XIrE6o2Jue9/0NF5GVmydqG7a+rJv1YZSiSeOjcc5aGYTMnFydNmMgwxee1JZME3d7kO6OTclEXEqmtoejk5DDJ9GXU+oYhjFQWBzpKLQyPrGjYsxwS+eK43WdC3cS8b/1F4TN89AWtbFmemfUrcWNCivy+ftiZKCoKSDb3mlLT6n642gaqrWjaN+W8xEiyvHuIH8sfLKtSDfV1dfqy1HN4WxrISIOP+y8Al0k+C73N3oU1DiYjD4ITq17mIjEdFy4mygEZE8/7m/EMIxhwuJIhxnRsraoZ7gWk4rjN+K1PRy9gQrjP9x0EaQnhzT3xM+PtxT2y0zFa2rmPNEK7es7CdOBJ/84gdtxaRp7PloAWHniNkbMPYzrsanwdLTC6uc74tnuDXUmja40yNKY6tiI3w5cx7FqjrSVBzZjKB8PHOtYHBVn96VoVWYDfeYZhmEMERZHOgz1bRneso7YXnFc+4Xx+gJZUVNDUxKW7w0O0PmJtS5D6VcLn2orUjwp1WjyH8cRnZyh9udJzczBa6vP4f/WXRCppD18XbH15W5oU88J+kK/ph4Y39ZLiPLXV58TDnu6RHCETKsLYHFUJko9li7Xj2k7pa5PAKfUMQxjuLA40nEmdpDGDNsuRojJKVM2yRnZ+Gr7ZbH9Uq/G8HBkq+6qQq5wfz7dHl5O1sIYYcofJ9U68b8SlYxhcw4JUUtpdG8N8MUfT7UTBhr6xvtDA0RaFjkkfrwpBLpCYno2wuNlL6amnpxWVxa+HlI8clrdwwsYR67KiCjXGzEMY8iwONJxmtVxRIu6jqK3y5rTbMzwKH7ZcxUxyZlo4GKLp7vW1/ZwDAbqB/XX0x3gYmchrHyfXXoKGdlVNx7451S4EEaUOuruYIm/n+2IF3v46G1jSTtLM/wwrgVo+GSksu1CBHQBpV6sbi1rONpo1wJd1/HzlJGjK1EpetG7qro4GBYjTEfqOdvAx81O28NhGIbRGCyO9ICJHeqpUuv4P+vSuRqdgj8Kes1QLxzuY6R+2+olU9sLAUA1cC//fRY5uXmVbsr7xj/n8Oaa88jIzkO3xi4ija59A/1JoyuNtvWd8EIPaYVOpiDRSepPQ6ysU12AJ6fUPYr6zraiCXd6di5ux2uuxk7f2Flg4U0mLZyqzDCMIcPiSA8Y0sIT9lZm4j/qw9ditT0cnYSK+T/eHCzc6Xr7ubGTkgYjmeQcZ2Fqgv9CovDeBjK+yK+wiCXTBYqEUoTl9b5NsHRqe7jYGU6B9yu9mwjjg4S0bLy19rzW3SYp2kewU92jodTOxu4yMsKmDJLcvHzsuVxQb8QpdQzDGDgsjvQAGwszjGoljRmWH2NjhpLYGRKFg2GxYtKuNOVkNEOnRs74eUJLIWxWngzHd/+FlvuxG87eFWl0oVHJQgxRU96XejfW2zS60rAwM8GP41uK632hMVimZUMVJa2OnerKh6+7fJ3YlEFy+laCEPpUf9iufi1tD4dhGEajsDjSE54oSK3beSkKUTqQpqNLUO3Lp1tl8fuz3RuI9C9Gswxo5onPR0rr6rl7r2FRQTpjWe/RO+vOY9aqIKRl5aJTQ2f8+0pXdG7kAkOlsbs9/m+An9j+fGsIrsekaGUc9NqHRcvnblqHxVFFHOvYlKGoS10vPzdh8c8wDGPI8K+cnuDrYS9W7Ci9YfXJcG0PR6egvjLkxOXhYCWK+ZnqYUJ7b7zZ31dsf7olRESFSoJEwch5R/D3iXDRPPLl3o1FxMjN3vCdBKd0ro+uPi6irurVVUHIrmSNVlXdAOl3g9z/6DvClN+UgcWRZFcIp9QxDGM8sDjSQ2OGv0/cFpMdBriTkIZ5+66K7f8N9hcd7pnq48UejTC1i3QFJIOFfaGyaFthy/l7GDbnMC5FJMHZ1kJYgr/Wt4mo6zAGKF3w27HN4WBlhnN3EjF3r/ysaqv5KxfSl38xirgZl6oWV0Z95lpMimjKbG5aA92bGG6kl2EYRoHFkR4xoJkHatmY415ixkOTUGPly38vi1X5Dg2cMLS5p7aHY3TQZPv9wQEY3rK2MMN4YdkZnLmdICaU72+4iJkrziIlMwft6zvh31e6oVtjVxgbno7W+KwgBZGs5s/eTtCOUx3XG5UbVztLEWmjNaiwKO2kQ+pa1KhjQ2fRmJxhGMbQYXGkR1iZm2JMm7pie7mWC7x1gSNXY7H1QoQwBvhoWFNeFddmdGRMCzzWxFXYHz+95CRGzz+Cv47dUkWXVjzbAe5GnNI1rEVtcaGI72urzyEtK0cLkSN2qisv9Fvi6y6jR5eM3JRBqTfqG8ApdQzDGAcsjvSwzoPYGxotUsqMFard+GhzsNie1LEe/Ll/i1YhV7b5k1qjpVdN3E/LFhNyinIuntoObw3w4yJuqssa3gyejla4EZuKL/69VC3PSWLscoSsm2Gnusql1hlz3VFcSqZwqiN6c70RwzBGAs9Y9IyGrnbo3MgZ1DZllREbM/x19JboYE8TcKphYXTDcn7xlHbi89nD11U0de3py/2mFBxtzPHd2BZie9mx22KBQ9PciE0R0TwbC1M0cGYXx4rAjnW0CBcjUgupeXCdmtbaHg7DMEy1wOJIj40ZqMeMNtyvtE1sSiZm77oitt/s74eaNhbaHhJTQC1bC6x4tiOWTG2P2jyZeoguPi54uksDsf3WmvOIT82qlpQ6iqwaWi8pTeNXEI025kawKpc6TqljGMaIYHGkh1DuNzXQjEnOVP3nZUx8uz0UyRk5aFbHAePbeWl7OAxTId4a4IvGbnbi+0u9n/IpDFwNTnVMxWjibies52kxhtLLjA0yVTkQFiO2+3JKHcMwRgSLIz2t7xjfThozrDhhXMYM58LvY/VpmU748bCmRmMJzRiWscrs8S2FNfKO4CisPVNyfyh1OtWxOKpcmqi3k43RptYdvR4nGjZTbyxaiGIYhjEWWBzpKY+38xarmgfDYnEzNhXGQF5ePj7YFCzqrUa1qoM29Zy0PSSGqRTN6jhiVh9ZK/fRpmCEx6vfXIUiUuxUVzUeONYlG3FKnRs7gTIMY1SwONJTvJxshHWy0hTWGFh75o6IHNlZmuH/BvppezgMUyWmP9YIbevVEn2gXl99Tu2NnakfGjkHmpnUQGN3O7We2/hMGYzLzpsWohQL7z6cUscwjJHB4sgAjBn+OX0HmTmG3cU9KSMbX2+/LLZf7u0DNyPumcMYBpQS+sO4lrC1MMWJm/FYePC6Ws8ffFem1DV2t4elmalaz21spgzGllZ38V4iopIyxWezUyNnbQ+HYRimWmFxpMf09HUVfVPI8Wr7xUgYMj/tCkNsShYautpiSmfp9sUw+o63sw0+HNpUbH//XyhCCtLg1AGbMaiv1xG1DaBoirGl1HVv4srCmmEYo4PFkR5DjTUVt7blxw03tS4sKhlLj9wU2zSRJEMKhjEUxratKxwos3Pz8eqqIOESpg5YHFWd+s62sDQzEb2ibmugLkxX2XlJ9uDilDqGYYwRnmUagDEDpeecuBEvRIShQUXlH20ORk5evphAKnVWDGMoULH7l6MC4WJngdCoZBFBUgchKqc6NmOoLKaF6rUuG0nd0Z2ENFyKSAIZgfb04ybODMMYHyyO9BwPRyv0LvgPzBCjRzuCI3H4apyIFr0/OEDbw2EYjUB9y74e3Vxs/37oBo5ci63S+RJSs4QhA+HvKVPDmMrh625czWB3F0SN2tZzgpMtN9hmGMb4YHFkAEzsKI0Z1p25g/QswzFmoL/l0y2XxPbz3RuK+gyGMVR6+7tjQntvYVX/xupzSEzPrvS5QiJklKOesw3srczVOEpjdqwzDnGkcqkL4KgRwzDGCYsjA6Cbjwu8nKyRlJGDLefvwVBYsP8a7t5PR21HK7zYw0fbw2EYjfPeYH8haCjqQ/2PKgs3f1Uffp7GI47IFfTY9TixzfVGDMMYKyyODAATkxpixdmQUuuoKSaJI+LdwQGwtmDHJMbwsbU0E/beVO+x/uzdSi92cPNX9TvW3YxLNajIfEkcuBIjjEHIFbShK/fGYhjGOGFxZCCMbeMFc9MaCAq/r1o11mc+33oJmTl56NTQGYMCPbQ9HIapNtrUq4WZPWWk9N31FxFZUDtUGXEUwJGjKuNqZylqb8jJOyw62SgsvPty1IhhGCOGxZGB4GpviX5NpYhYoefRo0NhsdgeHCmcoj4a1lS4eTGMMfFS78YIrOMo6o7eXHNOuDaWF4puXI9JEducVld16PfH193e4E0ZsnPzsOeyNGMgZ1CGYRhjhcWRATGxg0yt23D2LlIyc6Cv/0GTdTcxuWM9VUoLwxgT5qYmmD2+peixczAsFn8evVXux16KTBJRDlowcbO30ug4jQXld8iQ645O3UwQdasUJWvlXUvbw2EYhtEaLI4MCEpBa+hii9SsXGwMugt9hJq9Xo1OgbOtBV7t20Tbw2EYreHjZof/DfIX21/8e0l8L8oDN39VP4oduiGLo50FKXW9/NxE1J5hGMZYYXFkYOkfTxREj5Yfu12hVBxdICY5Ez/tChPbbw3whaM1WxAzxg1FT7s1dhH1d6+uChKR1fI3f2VxpC58PQy71xH9X7HzUqTYZpc6hmGMHRZHBsaYNnVFw1Tqc3Lujn4ZM3y9/TKSM3PQvK6jMJhgGGOHnCi/G9tCLBRcuJuIX3bLxYOyYKc69dPE3Q5U+hibkikuhkZYdArC49PF/x0kxhmGYYwZFkcGRk0bCwwJ9BTby4+Vv05B25y5nYA1p++I7Y+HNRWTQoZhAHcHK3wxMlBsz9l7FadvJZR6LEWWlOgGR47Uh42FGbydbAw2tU5JqevSyFnYyTMMwxgzLI4MkIkdZWrd5vP3kJiWDV0nLy9f1fCSIl9cDMwwRRnc3BMjW9URRguvrQ5CaimGK9diUpCVkwd7SzN41ZKTeUY9GLJj3a5LUhz1YZc6hmEYFkeGSGvvWvDzsEdGdh7WnZXRGF3mn9PhOH8nUUzo3h7gp+3hMIxOQrb2tR2tcCsuDZ9tvVTiMcF3ZUqdf20Hjr6qGT9PGYkLjZSvsaEQnZwh+uMRvf1YHDEMw7A4MnBjBup5pMvGDNTH5ZvtoWL7lT6Nhf0wwzAPQ3VH341rIWpf/j5xG7sLVvsLw051moMWnAwxrW7v5WjQfxFU6+nhyNbvDMMwLI4MlBGt6sDa3FQU2p68WXqNgraZvfMK4lKzhG3xU53ra3s4DKPTdG7kgmldG4jtt9eeR1wxc4BglVMdmzFoqtfRlagU5FJ+o4GwM0Q2fmWXOoZhGAmLIwPFwcocw1vWFtvLj+umMQOtwP5VYBrx0dCmovElwzBl83o/X1H/EpuShf9bd0EVGaZrcqkkOHKkfuo724qmvOnZubgdnwZDID0rF4euxohtFkcMwzASno0aMBM71BPX2y5EIj41C7oETeTIhIFWYAc09UBXto9lmHJhZW6K2eNbwty0hnAZ++eUrCskK+bkjBxhx0yRWEa9UGPUxu52BlV3dPhqrKhNrVPTWtXolmEYxtipkDj68ssv0a5dO9jb28PNzQ0jRoxAaKisF1HIyMjAjBkz4OzsDDs7O4wePRpRUUVz42/fvo3BgwfDxsZGnOfNN99ETk5R96V9+/ahdevWsLS0hI+PD5YsWVKVv9MoCazriMA6jsjKzcOa0+HQJf69EImj1+PESuy7g/21PRyG0SsCajuICBLx8eZg3I5LU6XUUVSJo7CawdfdsJrBKi51fQPcRa0qwzAMU0FxtH//fiF8jh07hp07dyI7Oxv9+vVDamqq6phXX30Vmzdvxj///COOv3fvHkaNGqXan5ubK4RRVlYWjhw5gqVLlwrh88EHH6iOuXHjhjimZ8+eCAoKwqxZszBt2jTs2LFDXX+30TCxkDEDWWbrAmlZOfh8a4jYnv5YI3gV9A9hGKb8PNutIdrXd0JqVq6w9z5/V6k34pQ6TaFEVwzBlIH+P9h1ieuNGIZhilMjvwpWZjExMSLyQyKoe/fuSExMhKurK1asWIExY8aIYy5fvgx/f38cPXoUHTt2xLZt2zBkyBAhmtzd5Q/yggUL8Pbbb4vzWVhYiO2tW7fi4sWLqud6/PHHcf/+fWzfvr1cY0tKSoKjo6MYk4OD8U4WqB9Kxy92IzkzB8ue6aAT6Ws//BeKn/dcFakcu19/TKQJMQxTccLj0zDwp4NIycyBlbmJSJH6dHhTTO7E5iaa4GBYDCYvOoGGLrbY80YP6Kso2nkpCnP3XlW1UDj9fl+RjskwDGPIlFcbVOnXkE5OODk5ievTp0+LaFKfPn1Ux/j5+cHb21uII4KuAwMDVcKI6N+/vxhwcHCw6pjC51COUc5REpmZmeIchS8MRLdzcq7TFWMGSv9ZcOC62H5/iD8LI4apAhR1pf5HBAkjJeWO0axj3c24VGFmoE9QfefGoLtCTD//12khjEhQvzfEn4URwzBMISr9i5iXlyfS3bp06YJmzZqJ+yIjI0Xkp2bNmkWOJSFE+5RjCgsjZb+yr6xjSPCkp6eXWg9FalC5eHl5VfZPMziUnkdUvB2dlKHVsXy6NQRZOXno6uOC/k09tDoWhjEERreuI0xNCCob8fNgcaQpXO0s4WRrAcpQDovWj9Q6+r1dfTIcvb/fh1dWBiE0Khl2lmZ4sUcjHHq7F8a3k/8/MAzDMBIzVBKqPaK0t0OHDkEXeOedd/Daa6+pbpOQYoEk8fd0QJt6tXD6VgJWnwrHzF6NtTKO/VdihEAzM6mBD4cGcAEww6gB+h59MSoQEUkZ8PewF9FiRnOvNRlekJkMmTI0r1t0IVCXyMjOFb/3C/Zdw71EuShW08YcT3dpgKc61Yejjbm2h8gwDKOTVOp/0ZkzZ2LLli04cOAA6tatq7rfw8NDGC1QbVDh6BG51dE+5ZgTJ04UOZ/iZlf4mOIOd3Sb8gOtra1LHBO52tGFKd2YgcTR3yfC8UIPH2FLW92rl+SqRVCz18bubBvLMOqCohkbZ3TR9jCMAj9PKY501ZSB6kwphfq3AzcQW9Ak2NXeEs91ayiyCFg8MwzDqDGtjrwbSBitX78ee/bsQYMGslO7Qps2bWBubo7du3er7iOrb7Lu7tSpk7hN1xcuXEB0tHTJIcj5joRPQECA6pjC51COUc7BVJxBgZ5wtDbH3fvpOHBFNv2rTpYcuYHrMalwsbPEK320E7liGIapKn4FdUe6Jo4S07Lx064wdPl6D77497IQRmR6QwYdB9/qiWe7N2RhxDAMUw7MKppKR050GzduFL2OlBohqvGhiA5dP/PMMyK9jUwaSPC89NJLQtSQUx1B1t8kgiZPnoxvvvlGnOO9994T51YiP9OnT8ecOXPw1ltv4emnnxZCbPXq1cLBjqkcZHwwpk1dLDp0Q6wq9vRzq7bnpjon+k+beHuALxysOJ2DYRj9xNdDt3odkQii3/W/jt4SroVEAxdbvNCjEUa0rMNmCwzDMJoUR/PnzxfXPXoUtTBdvHgxpkyZIrZnz54NExMT0fyVHOTIZW7evHmqY01NTUVK3gsvvCBEk62tLZ566il88sknqmMoIkVCiHom/fTTTyJ17/fffxfnYioPpVTQf6J7LkeLCBKtKlYHX227LHqxtPSqidGtH6RhMgzD6BtN3O2E8QWJErpQNFwbRCSm47cD1/H3idsqp0Kqh5rRyweDAz2rPXWaYRjGUKhSnyNdhvsclcyE346JfPmXe/ngtX6+Gn++07fiMXr+UTGZ2PBiF7Tw0t0CZoZhmPLw2Ld7cSsuDcundUAXH5dqb4cwf/81rDkdjuxc+d93i7qOmNHTRzRzNWFRxDAMUyVtwAnIRhg9InG08mQ4XurdGOamJhrtq/HhJmnCMK6NFwsjhmEMAorQkDii1LrqEkdXo5Mxb+81bDx3T/y2Eu0bOGFmTx90a+zC7p8MwzBqgsWRkUG9hZxtLRCdnIndl6IxoJnmeg2tOhmOi3eTYG9lhjcHaD5KxTAMUx34eTrgv5AohEZqvtn4xbuJmLfvKrZdjISS59G9iasQRSSOGIZhGPXC4sjIoOLcce28MH/fNWHMoClxdD8tC9/uuCy2X+3TRGt5+QzDMProWEetF+bsCcPe0Afuov0C3DGzl49O91diGIbRd1gcGSET2nljwf5rOBgWi1txqajnbKv25/hh5xUkpGWL4uXJneqp/fwMwzDawlcRR1HJIsVNXeYHVAJ89FocftlzVaQ/E3TqIc1ri5oi5XkZhmEYzcHiyAjxdrZBt8auot8RNYX9v4F+aj3/pYgkLDt2S2x/NKypRuuaGIZhqpv6zrawNDMRLnG349OEdXZVRRG5iM7ZexVnb98X95mb1sCoVnUxvUejKp+fYRiGKT8sjoyUiR28hTj651Q4Xu3bGJZmpmo5L/0nTyYMVC9MdrKdG1WvkxPDMIymoUhRY3c7UVNJdUeVFS8Uddp+MRJz915FSISsXyLR9Xg7Lzz3WKNqa7fAMAzDPIDFkZHS288N7g6WiErKxI7gKAxrUVst5918PgInbsTDytwE/xvsr5ZzMgzD6Bp+Hg5CHJFj3YBmnhV6bHZuHjYF3RNGC9diUsV9thammNSxHp7p1gBu9lYaGjXDMAzzKFgcGSlmprQ66Y2fdodh+bFbahFHqZk5+GLrJbH9Yg8fXvVkGMZgqYwpQ2ZOLtacviNqPsPj08V9DlZmmNKlAaZ2ro9athYaGy/DMAxTPlgcGTGPt/fCL3vCcPxGPK5Gp8DHza5K56NV0MikDHg5WeO57g3VNk6GYRidNWUohzhKy8oR9Z2/HbgmovUEtVSY1q0hJnX0hr2VucbHyzAMw5QPFkdGjKejNXr5uWPXpSisOH4bHwwNqPS5bsamYuGBG2L7/cEBsDJXTw0TwzCMLoujG3GpSM/KhbXFw795SRnZ+OvoLSw6dAPxqVniPg8HKzz/WEMRuS/pMQzDMIx2YXFk5Ezs6C3E0ZrT4XhrgG+lRc2nW0KQlZsnmhP2DXBX+zgZhmF0CVc7SzjZWgjRExadXKT3UEJqFhYfvoHFR24iOSNH3OftZIMXejTCqNZ11GaAwzAMw6gfFkdGTvfGrqI26O79dGw5H4ExbepW+Bx7L0dj9+VomJnUwAdDAlCjhnp6fjAMw+gq9DtHdUdHrsUJUwYSR9FJGVh48DqWH7+NtKxccRylK8/o2QhDm9cWtZ4MwzCMbsPiyMghS9onOnjj2x2hWHH8VoXFERUYf7IlRGw/3bVBleuWGIZh9Cm1jsTRobBYXLiTiFWnwpGVkyf2Na3tgJk9fdC/qQdM1NQklmEYhtE8LI4YjG1bF7N3XsGZ2/cRci8JAbUdyv3YPw7dxI3YVLjaW+KlXj4aHSfDMIwuOtZtOndPdV+berWEKOrh68pRdIZhGD2EY/yM6KlBq5vEihO3yv24yMQM4XZHvDPQjx2XGIYxKlp514Kif7r4OOPvZztizfRO6OnnxsKIYRhGT+HIESOg1LqtFyKw4ew9vDPQH7aWj/5ofLntksirb+1dEyNa1qmWcTIMw+gKTdztsfLZjrCxMENgXUdtD4dhGIZRAxw5YgSdGjqjgYstUjJziqSIlMbJm/HYGHRPrJp+MrwZ59QzDGOUdGjozMKIYRjGgGBxxAhI3DzR3ltsLzt2C/n5+aUem5uXjw83Bott6tXRrA5PDBiGYRiGYRj9h8URo2J0m7qwMDNB8L0knL+TWOpxK07cRkhEEhyszPBmf99qHSPDMAzDMAzDaAoWR4wKamg4qJk0Zlh+vGRjBmpu+P1/oWL79X6+4jEMwzAMwzAMYwiwOGKKMLFjPXG9+VwEEtOzH9r//c5Q3E/LFha2EzvINDyGYRiGYRiGMQRYHDFFaFuvFpq42yE9Oxcbzt4tsi/4XiJWHL8ttj8a1pS7vTMMwzAMwzAGBc9umSJQb46JHeqpUusUYwa6/mhTMPLygaEtaqNjQ2ctj5RhGIZhGIZh1AuLI+YhRrSqAytzE1yJSsGpWwniPrLtPnkzAdbmpvjfID9tD5FhGIZhGIZh1A6LI+YhHK3NMaxFbbFNaXTU++iLfy+J2zN7+cDT0VrLI2QYhmEYhmEY9WP2/+3deUhWexrA8UcztQm1bdLMtAXJymrajJahYYoinJqIisJKkvkjsMkWwiisP1psodWi7Y/+av0j24YIK7GCzPaSyorELKckqLSi5eoZnt+LkWH3Mozn/d057/cD9npevZfnPp17zvv8lue48O+EB+jSuqPXn8u/7v3bzCJV136WhPZ/kH/8uZvt0AAAAABXMHOEJvWLi5I+sZHy5Zd6OVRSad5b8bfeEhbSwnZoAAAAgCsojvCbjRnUX3r+Uf6a1NFqTAAAAICbKI7wU3//U6x5yGtYSLCZNdKCCQAAAPAq9hzhp1qHhcipf46Ur7/US9cOrW2HAwAAALiK4gi/qnMbOtMBAAAgMLCsDgAAAAAojgAAAADAh+IIAAAAACiOAAAAAMCH4ggAAAAAKI4AAAAAwIfiCAAAAAAojgAAAADAh+IIAAAAACiOAAAAAMAnRDzKcRzzWlNTYzsUAAAAABY11AQNNULAFUe1tbXmtUuXLrZDAQAAAPA7qRGioqJ++vMg57fKp/9T9fX1UlVVJRERERIUFGS9UtUirbKyUiIjI63GEkjIux3k3Q7ybgd5t4O820He7SDvzUNLHi2MYmNjJTg4OPBmjvQ/Oi4uTn5P9ITmpPY/8m4HebeDvNtB3u0g73aQdzvI+//u12aMGtCQAQAAAAAojgAAAADAh+LID8LCwmTlypXmFf5D3u0g73aQdzvIux3k3Q7ybgd59y/PNmQAAAAAgP8GM0cAAAAAQHEEAAAAAD4URwAAAABAcQQAAAAAPhRHAAAAAEBx5B87d+6Url27Snh4uAwdOlRKSkpsh+Rpubm5MmTIEImIiJCOHTvKpEmTpKyszHZYAWXdunUSFBQkCxYssB2K57148UJmzpwp7du3l1atWknfvn3l+vXrtsPytLq6OsnJyZFu3bqZnPfo0UNWrVolNH9tfhcvXpQJEyZIbGysuaYcP3680c815ytWrJBOnTqZv4sxY8bI48ePrcXr9Zx//fpVsrOzzXWmdevW5ndmz54tVVVVVmMOhHP9e3PnzjW/s3XrVr/GGCgojlx25MgRWbRokelPf/PmTenfv7+MGzdOqqurbYfmWUVFRZKZmSnFxcVSUFBgLuZjx46VDx8+2A4tIFy7dk327Nkj/fr1sx2K571580ZGjBghLVu2lDNnzsj9+/dl06ZN0rZtW9uhedr69etl165dsmPHDnnw4IE53rBhg+Tl5dkOzXP0uq33TR1kbIrmffv27bJ79265evWq+cCu99hPnz75PdZAyPnHjx/NZxkdHNDXY8eOmcHHiRMnWok1kM71Bvn5+ebzjRZRcIk+5wjuSUlJcTIzM78d19XVObGxsU5ubq7VuAJJdXW1Duc6RUVFtkPxvNraWicxMdEpKChwRo0a5WRlZdkOydOys7OdkSNH2g4j4KSmpjoZGRmN3ps8ebKTlpZmLaZAoNfx/Pz8b8f19fVOTEyMs3Hjxm/vvX371gkLC3MOHTpkKUpv57wpJSUl5vcqKir8Fleg5v358+dO586dndLSUichIcHZsmWLlfi8jpkjF3358kVu3LhhpvkbBAcHm+MrV65YjS2QvHv3zry2a9fOdiiepzN2qampjc55uOfkyZMyePBgmTp1qllCOmDAANm3b5/tsDxv+PDhcv78eXn06JE5vnPnjly+fFnGjx9vO7SAUl5eLi9fvmx0vYmKijLL17nH+vceq0u82rRpYzsUT6uvr5dZs2bJkiVLpE+fPrbD8bQQ2wF42evXr83a9Ojo6Ebv6/HDhw+txRVoFxPd96JLj5KTk22H42mHDx82yyx0WR384+nTp2Z5ly7dXbZsmcn9/PnzJTQ0VNLT022H51lLly6VmpoaSUpKkhYtWpjr/Jo1ayQtLc12aAFFCyPV1D224Wdwly5f1D1IM2bMkMjISNvheJou3w0JCTHXeLiL4gien8koLS01o7pwT2VlpWRlZZk9Xtp4BP4r/nXmaO3ateZYZ470fNf9FxRH7jl69KgcOHBADh48aEZwb9++bQZhdA8AeUeg0P2806ZNM00xdJAG7tFVSNu2bTMDkDpLB3exrM5FHTp0MKOKr169avS+HsfExFiLK1DMmzdPTp8+LYWFhRIXF2c7HM9fuLXJyMCBA83Iln5pYwzdKK3f68g6mp926Ordu3ej93r16iXPnj2zFlMg0GUtOns0ffp007VLl7osXLjQdMqE/zTcR7nH2iuMKioqzKAYs0buunTpkrnHxsfHf7vHau4XL15suiGjeVEcuUiXtgwaNMisTf9+pFePhw0bZjU2L9NRLC2MtKPLhQsXTLtduGv06NFy7949M4Le8KUzGrrMSL/XQQI0P10u+mObet0Hk5CQYC2mQKAdu3T/6Pf0HNfrO/xHr+1aBH1/j9Xljtq1jnus+4WRtkw/d+6ceYwA3KUDMHfv3m10j9WZah2oOXv2rO3wPIdldS7TvQC6zEI/KKakpJie9Nqucc6cObZD8/RSOl3ucuLECfOso4a157pRV5+Dgeanef5xT5e21NWbJnu93KOzFdocQJfV6YcVfYba3r17zRfco88i0T1GOoqry+pu3bolmzdvloyMDNuhec779+/lyZMnjZow6AdDbbCj+dfljKtXr5bExERTLGmLaf3QqM+3Q/PnXGerp0yZYpZ36coMXRXQcI/Vn+ugMNw5138sQvURDjo40LNnTwvRepztdnmBIC8vz4mPj3dCQ0NNa+/i4mLbIXmantZNfe3fv992aAGFVt7+cerUKSc5Odm0L05KSnL27t1rOyTPq6mpMee2XtfDw8Od7t27O8uXL3c+f/5sOzTPKSwsbPJ6np6e/q2dd05OjhMdHW3+Hxg9erRTVlZmO2zP5ry8vPyn91j95+Deuf4jWnm7J0j/sF2gAQAAAIBt7DkCAAAAAIojAAAAAPChOAIAAAAAiiMAAAAA8KE4AgAAAACKIwAAAADwoTgCAAAAAIojAAAAAPChOAIAAAAAiiMAAAAA8KE4AgAAACAQ+Q/5ifyd7dGDoAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 训练损失曲线\n",
    "plt.plot(train_loss_list)\n",
    "plt.title('训练损失曲线', fontproperties=chinese_font)\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.show()\n",
    "\n",
    "# 测试集预测\n",
    "y_pred = model(X_test).detach().cpu().numpy()\n",
    "y_test_np = y_test.cpu().numpy()\n",
    "\n",
    "# 反归一化\n",
    "y_pred_rescaled = scaler.inverse_transform(y_pred.reshape(-1, 1))\n",
    "y_test_rescaled = scaler.inverse_transform(y_test_np.reshape(-1, 1))\n",
    "\n",
    "# 可视化预测结果\n",
    "plt.figure(figsize=(10, 4))\n",
    "plt.plot(y_test_rescaled, label='real')\n",
    "plt.plot(y_pred_rescaled, label='predict')\n",
    "plt.legend()\n",
    "plt.title('PyTorch LSTM预测结果对比', fontproperties=chinese_font)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
